Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is in reply to the application filed on October 2, 2024.
2. Claim(s) 1-31 are currently pending and have been examined.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Independent Claim(s) 1 and 13 are directed to an abstract idea consisting of systems and methods for predicting cosmetic dermatology treatment plans and human skin characteristics with artificial intelligence.
Independent Claim 1 recites “receiving input from a user specifying patient characteristics including a skin condition needing treatment; predict a cosmetic dermatology treatment plan based on the user-specified patient characteristics; and display the predicted cosmetic dermatology treatment plan to the user.”
Independent Claim 13 recites “receive data that indicates skin characteristics of a patient; maintain an expert system knowledge base for operating a therapeutic laser; determine settings for the therapeutic laser based on the expert system knowledge base and the skin characteristics of the patient; and a user interface configured to present the determined settings for treating the patient.”
The limitations of Claims 1 and 13, as drafted, under its broadest reasonable interpretation, covers the performance of a Mental Process which are concepts performed in the human mind (including an observation, evaluation, judgment, opinion), but for the recitation of generic computer components. That is, other than reciting, “system inference engine, system knowledge base, user interface, display, processor and memory” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “processor and memory” language, “receive” in the context of this claim encompasses the user manually retrieving data that indicates skin characteristics of a patient. Similarly, the determining settings based on the knowledge and the skin characteristics of the patient, covers performance of the limitation in the mind, but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of using a “system inference engine, system knowledge base, user interface, display, processor and memory” to perform all of the “receiving, applying, controlling, maintaining, determining, presenting” steps. The “system inference engine, system knowledge base, user interface, display, processor and memory” is/are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) of executing computer-executable instructions for implementing the specified logical function(s) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claim 1 has the following additional elements (i.e., system inference engine, system knowledge base, user interface, display). Claim 13 has the following additional elements (i.e., processor and memory comprising an expert inference engine). Looking to the specification, these components are described at a high level of generality (¶ 31 and 37; The functional units described in this specification have been labeled as computing devices. A computing device may be implemented in programmable hardware devices such as processors, digital signal processors, central processing units, field programmable gate arrays, programmable array logic, programmable logic devices, cloud processing systems, or the like. The computing devices may also be implemented in software for execution by various types of processors. As referred to herein, the terms “computing device” and “entities” should be broadly construed and should be understood to be interchangeable. They may include any type of computing device, for example, a server, a desktop computer, a laptop computer, a smart phone, a cell phone, a pager, a personal digital assistant (PDA, e.g., with GPRS NIC), a mobile computer with a smartphone client, or the like). The use of a general-purpose computer, taken alone, does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
It is worth noting that the above analysis already encompasses each of the current dependent claims (i.e., claims 2-12 and 14-31). Particularly, each of the dependent claims also fails to amount to “significantly more’ than the abstract idea since each dependent claim is directed to a further abstract idea, and/or a further conventional computer element/function utilized to facilitate the abstract idea. Accordingly, none of the current claims implements an element—or a combination of elements—directed to an inventive concept (e.g., none of the current claims is reciting an element—or a combination of elements—that provides a technological improvement over the existing/conventional technology). These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Mental Processes,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Claims 1-31 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-31 are rejected under 35 U.S.C. 103 as being unpatentable over Pub. No. US 2021/0315512 A1 to DEPFENHART et al. in view of Pub. No.: US 2022/0339465 A1 to ARAÚJO MARTINS VILAÇA et al. ARAÚJO MARTINS VILAÇA ET AL.
As per claim 1, DEPFENHART ET AL. discloses a method comprising (cosmetic method involves dividing a person's skin into a plurality of zones; evaluating zones predetermined skin characteristics in each zone - assigning a skin status quo code by utilizing the collective score for each predetermined skin characteristic, Abstract, cosmetic method and system of scoring a person's skin, a cosmetic product and genetic profile and utilizing the scoring to customize a cosmetic intervention, see DEPFENHART ET AL. para [0001], see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], see DEPFENHART ET AL. para [0074]-[0082], Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles - Dryness - Sensitivity -redness in the skin - Pigmentation, see DEPFENHART ET AL. para [0115]-[0124], see DEPFENHART ET AL. para [0135]-[0150], system is operable remote from an aesthetic practitioner, is capable of storing data related to individuals including profiles, which may include the skin status quo code based analysis - weighting and scoring is an artificial intelligence based system - This systematic, defined, reproducible cosmetic intervention tool aims to bridge the gap between various treatment modalities and sustained skin health. Cosmetic interventions can include products that can quickly be developed to use in conjunction with emerging aesthetic treatment modalities, see DEPFENHART ET AL. para [0200]-[0210]):
-- receiving input specifying patient characteristics including a skin condition needing treatment (Abstract, see DEPFENHART ET AL. para [0001], see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], "Skin characteristics" typically refers to a feature or quality belonging to a person - used interchangeably include terms "skin see DEPFENHART ET AL. parameters", "skin conditions" Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles - Dryness - Sensitivity - redness in the skin Pigmentation, see DEPFENHART ET AL. para [0115]-[0124]);
-- applying an expert system inference engine to an expert system knowledge base to predict a cosmetic dermatology treatment plan based on the user-specified patient characteristics (see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles - Dryness - Sensitivity - redness in the skin - Pigmentation, see DEPFENHART ET AL. para [0115]-[0124], see DEPFENHART ET AL. para [0140]-[0150], system is operable remote from an aesthetic practitioner, is capable of storing data related to individuals including profiles, which may include the skin status quo code based analysis - weighting and scoring is an artificial intelligence based system This systematic, defined, reproducible cosmetic intervention tool aims to bridge the gap between various treatment modalities and sustained skin health. Cosmetic interventions can include products that can quickly be developed to use in conjunction with emerging aesthetic treatment modalities, see DEPFENHART ET AL. para [0200]-[0210]); and
-- controlling a user interface to display the predicted cosmetic dermatology treatment plan to the
user (utilizing the skin status quo code of the method - determining the at least one predetermined skin
characteristic that may benefit from a cosmetic intervention; and recommending at least one cosmetic
intervention to effect the predetermined skin characteristic, see DEPFENHART ET AL. para [0037]-[0046], The recommendation module is further capable of executing instructions to prepare recommendations of specific cosmetic code based products and preparing and processing an output to an end user which may be the individual subject or an aesthetic practitioner, see DEPFENHART ET AL. para [0200]-[0210]) but fails to specifically disclose receiving input from a user regarding a skin condition.
However, ARAÚJO MARTINS VILAÇA ET AL. in analogous art discloses receiving input from a user regarding a skin condition (laser skin treatment of skin features, Abstract, see DEPFENHART ET AL. para [0030]-[0040], the implementation of a fully-automatic, robust and accurate strategy for the location and segmentation of vascular lesions within the planned time of work may be not straightforward. Therefore, and as a backup plan, development of semi-automatic tools, where the operator provides small user input to detect the target region, are also valid solution in order to successfully develop the full extent of the described disclosure, see DEPFENHART ET AL. para [0106]-[0115], see DEPFENHART ET AL. para [0116]-[0124]).
It would have been obvious to one of ordinary skill in the art to add ARAÚJO MARTINS VILAÇA ET AL.'s treatment guidance visualization and evaluation to DEPFENHART ET AL.'s method/system as it controls the correct handling of a laser equipment during the treatment may minimize the side effects of this treatment, while improving its effectiveness, see DEPFENHART ET AL. para [0116]-[0124].
As per claim 2, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising receipt of one or more patient photographs from a user followed by application of a machine learning classification model to the photograph(s) to predict skin features of a patient, with the predicted skin features serving as additional input to the expert system for prediction of a cosmetic dermatology treatment plan (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an arca of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060], see DEPFENHART et al. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 3, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising an expert system in which Fitzpatrick skin type, a scale ranging from Type 1 to Type 6 skin, is a patient characteristic that affects the predicted cosmetic dermatology treatment plan (evaluation criteria and scale of scores for the skin characteristic of sensitivity, corresponding to specific see DEPFENHART ET AL. parameters (50) are illustrated in FIG. 5A. The presentation of visible inflammation and redness in the skin have associated scale of scores of 1 (51) to 5 (55) - Flushed cheeks, scaling and fine bumps are common indicators of inherent sensitivity. In Fitzpatrick Type V and VI, this see DEPFENHART ET AL. parameter would be described by taking an image using the VISIAᵀ system (or similar) to visualize inherent redness masked by melanin, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 4, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising an expert system in which Kesty Redness, a scale for defining skin redness comprised of values 0=clear, 1=almost clear, 2=mild, 3=moderate, 4=severe, is a patient characteristic that affects the predicted cosmetic dermatology treatment plan (evaluation criteria and scale of scores for the skin characteristic of sensitivity, corresponding to specific see DEPFENHART ET AL. parameters (50) is illustrated in FIG. 5A. The presentation of visible inflammation and redness in the skin have associated scale of scores of 1 (51) to 5 (55). Wherein a score of 1 is none or barely perceivable redness, to a score of 5 being representative of permanent red patches, a skin that flushes easily, with significant number of broken capillaries, raised scaly patches or bumps. A common area in which this is observed is the nose and cheeks in zone 2 (22). Telangiectasias or broken capillaries contribute towards a high scoring in this area. Flushed cheeks, scaling and fine bumps are common indicators of inherent sensitivity, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 5, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising an expert system in which Kesty Pigmentation, a scale for defining skin pigmentation comprised of values 0=none, 1=mild, 2=moderate, and 3=severe, is a patient characteristic that affects the predicted cosmetic dermatology treatment plan (each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 6, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising an expert system in which the Glogau Wrinkle Scale, a scale ranging from Type 1 to Type 4, and/or Fitzpatrick Wrinkle Severity Scale, a scale ranging from 1 = least wrinkles to 9 = most wrinkles, is a patient characteristic that affects the predicted cosmetic dermatology treatment plan (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], In Fitzpatrick Type V and VI, this see DEPFENHART ET AL. parameter would be described by taking an image using the VISIAᵀ system (or similar) to visualize inherent redness masked by melanin, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claims 7 and 28, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method/system further comprising a machine learning classification model that is a convolutional neural network, Transformer, or neural network model that combines convolution and attention (a Deep Learning (DL) strategy has been used to locate and segment all vascular lesions. Here, a convolutional neural network (CNN) architecture that allows a stable performance was designed and further trained, see ARAÚJO MARTINS VILAÇA ET AL. para [0106]-[0115]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 8, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising a multi-label machine learning classification model that is trained to receive as input one or more patient photographs and predict all of the following skin features simultaneously: Fitzpatrick skin type, Kesty Redness, Kesty Pigmentation, Glogau Wrinkle Scale, and Fitzpatrick Wrinkle Severity Scale (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an area of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060], comprise databases which may include a plurality of weighting tables; and a set of instructions directed to at least one of a plurality of predictive equations for scoring a skin status quo code, a intrinsic code, a cosmetic code, a second unique code or a set of instructions to utilize a selection of the codes to make a cosmetic recommendation, see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 9, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method further comprising a machine learning classification model that is a convolutional neural network ending in one fully connected layer, upon which a gradient-based neural network explanation method is applied; and a user interface in which the visual explanations are displayed to a user in order to explain which regions of the input image were used to make skin feature predictions (a Deep Learning (DL) strategy has been used to locate and segment all vascular lesions. Here, a convolutional neural network (CNN) architecture that allows a stable performance was designed and further trained, see ARAÚJO MARTINS VILAÇA ET AL. para [0106]-[0115], laser handling assistance is foreseen using a collaborative robot (i.e. LBR Med), helping the physician to guarantee the optimal relation laser/patient's skin over the treatment session - different control strategies has been developed to: 1) keep the distance/angle between laser/patient's skin; 2) force the laser positioning at the vessel's center when near; 3) disable the laser when outside the lesion; and, 4) keep the laser under the limits of pathologic vein that is being treated, see ARAÚJO MARTINS VILAÇA ET AL. para [0116]-[0124]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 10, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method in which the cosmetic dermatology treatment plan includes one or more descriptions of therapeutic laser settings (laser skin treatment of skin features, Abstract, laser therapy has been implemented and is now widely used for the treatment of several vascular lesions - selectively target specific structures is made possible by adjusting several laser parameters, including its wavelength, spot size, cooling, pulse time, and power, see ARAÚJO MARTINS VILAÇA ET AL. para [0004]-[0006], see ARAÚJO MARTINS VILAÇA ET AL. para [0023]-[0029], see ARAÚJO MARTINS VILAÇA ET AL. para [0030]-[0040], see ARAÚJO MARTINS VILAÇA ET AL. para [0106]-[0115], laser handling assistance is foreseen using a collaborative robot (i.e. LBR Med), helping the physician to guarantee the optimal relation laser/patient's skin over the treatment session - different control strategies has been developed to: 1) keep the distance/angle between laser/patient's skin; 2) force the laser positioning at the vessel's center when near; 3) disable the laser when outside the lesion; and, 4) keep the laser under the limits of pathologic vein that is being treated, see ARAÚJO MARTINS VILAÇA ET AL. para [0116]-[0124]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 11, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method in which the cosmetic dermatology treatment plan is a description of how to use injectable medication for wrinkle relaxation, including the type of medication, the anatomical locations for the injections, and the dose for each injection site (aesthetic practitioner and may recommend specific cosmetic interventions such as Botulinum toxin (to reduce lines associated with frowning in the harsh sun), micro needling with platelet rich plasma to address both wrinkling and pigmentation or laser to remove pigmentation spots, see DEPFENHART ET AL. para [0193]-[0201]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 12, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a method in which the expert system knowledge base includes a mapping between a patient's age or wrinkle severity score and in which the one or more cosmetic dermatology treatment plans include a visual diagram of a human face with annotations on the face indicating the anatomical locations for the injections and the dose for each injection site (FIG. 5B is a representative visual skin guide for the scoring, for scores 2 to 5 for sensitivity, and is denoted by reference (52) to (55), sensitivity visual guide for sensitivity for score 1 is an absence of redness and therefore not shown in the visual guide, see DEPFENHART ET AL. para [0135]-[0145], The data input may also be a visual image in the form of a photographic image or video images of a person or input data may be data derived from processing and related to specific predetermined skin characteristics. The skin-scoring module further has a means to process and assess the data input (1412) on the basis of a set of weight related tables (1415) to apply scores for each of the predetermines skin characteristics (1413) and to derive a skin status quo code (1414), see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 1, and incorporated herein.
As per claim 13, DEPFENHART ET AL. discloses a system comprising (cosmetic method involves dividing a person's skin into a plurality of zones; evaluating zones predetermined skin characteristics in each zone - assigning a skin status quo code by utilizing the collective score for each predetermined skin characteristic, Abstract, cosmetic method and system of scoring a person's skin, a cosmetic product and genetic profile and utilizing the scoring to customize a cosmetic intervention, see DEPFENHART ET AL. para [0001], see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles - Dryness - Sensitivity - redness in the skin- Pigmentation, see DEPFENHART ET AL. para [0115]-[0124], see DEPFENHART ET AL. para [0140]-[0150], system is operable remote from an aesthetic practitioner, is capable of storing data related to individuals including profiles, which may include the skin status quo code based analysis - weighting and scoring is an artificial intelligence based system. This systematic, defined, reproducible cosmetic intervention tool aims to bridge the gap between various treatment modalities and sustained skin health. Cosmetic interventions can include products that can quickly be developed to use in conjunction with emerging aesthetic treatment modalities, see DEPFENHART ET AL. para [0200]-[0210]):
-- at least one processor and memory comprising an expert inference engine configured to (see DEPFENHART ET AL. para [0140]-[0150], system is operable remote from an aesthetic practitioner, is capable of storing data related to individuals including profiles, which may include the skin status quo code based analysis – weighting and scoring is an artificial intelligence-based system - This systematic, defined, reproducible cosmetic intervention tool aims to bridge the gap between various treatment modalities and sustained skin health. Cosmetic interventions can include products that can quickly be developed to use in conjunction with emerging aesthetic treatment modalities, see DEPFENHART ET AL. para [0200]-[0210]):
-- receive data that indicates skin characteristics of a patient (Abstract, see DEPFENHART ET AL. para [0001], see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], "Skin characteristics" typically refers to a feature or quality belonging to a person – used interchangeably include terms "skin see DEPFENHART ET AL. parameters", "skin conditions" - Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles - Dryness - Sensitivity redness in the skin - Pigmentation, see DEPFENHART ET AL. para [0115]-[0124]);
-- maintain an expert system knowledge base for operating a therapeutic laser (aesthetic practitioner and may recommend specific cosmetic interventions such as Botulinum toxin (to reduce lines associated with frowning in the harsh sun), micro needling with platelet rich plasma to address both wrinkling and pigmentation or laser to remove pigmentation spots, see DEPFENHART ET AL. para [0193]-[0201]); and
-- a user interface configured to present the determined settings for treating the patient (utilizing the skin status quo code of the method - determining the at least one predetermined skin characteristic that may benefit from a cosmetic intervention; and recommending at least one cosmetic intervention to effect the predetermined skin characteristic, see DEPFENHART ET AL. para [0037]-[0046], The recommendation module is further capable of executing instructions to prepare recommendations of specific cosmetic code based products and preparing and processing an output to an end user which may be the individual subject or an aesthetic practitioner, see DEPFENHART ET AL. para [0200]-[0210]) but fails to specifically disclose determine settings for the therapeutic laser based on the expert system knowledge base and the skin characteristics of the patient.
However, ARAÚJO MARTINS VILAÇA ET AL. in analogous art discloses determine settings for the therapeutic laser based on the expert system knowledge base and the skin characteristics of the patient (laser skin treatment of skin features, Abstract, laser therapy has been implemented and is now widely used for the treatment of several vascular lesions - selectively target specific structures is made possible by adjusting several laser see DEPFENHART ET AL. parameters, including its wavelength, spot size, cooling, pulse time, and power, see DEPFENHART ET AL. para [0004]-[0006], see DEPFENHART ET AL. para [0023]-[0029], see DEPFENHART ET AL. para [0030]-[0040], see DEPFENHART ET AL. para [0106]-[0115], laser handling assistance is foreseen using a collaborative robot (i.e. LBR Med), helping the physician to guarantee the optimal relation laser/patient's skin over the treatment session - different control strategies has been developed to: 1) keep the distance/angle between laser/patient's skin; 2) force the laser positioning at the vessel's center when near; 3) disable the laser when outside the lesion; and, 4) keep the laser under the limits of pathologic vein that is being treated, see DEPFENHART ET AL. para [0116]-[0124]).
It would have been obvious to one of ordinary skill in the art to add ARAÚJO MARTINS VILAÇA ET AL.'s treatment guidance
visualization and evaluation to DEPFENHART ET AL.'s method/system as it controls the correct handling of a laser equipment during the treatment may minimize the side effects of this treatment, while improving its effectiveness, see DEPFENHART ET AL. para [0116]-[0124].
As per claim 14, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the data indicates a patient skin characteristic needing treatment (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an area of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060], comprise databases which may include a plurality of weighting tables; and a set of instructions directed to at least one of a plurality of predictive equations for scoring a skin status quo code, a intrinsic code, a cosmetic code, a second unique code or a set of instructions to utilize a selection of the codes to make a cosmetic recommendation, see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 15, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data includes user input information about the skin characteristics of the patient (Abstract, see DEPFENHART ET AL. para [0001], see DEPFENHART ET AL. para [0021]-[0031], see DEPFENHART ET AL. para [0052]-[0060], "Skin characteristics" typically refers to a feature or quality belonging to a person - used interchangeably include terms "skin see DEPFENHART ET AL. parameters", "skin conditions" - Cosmetic interventions are generally known in the art and may be invasive or non-invasive aesthetic treatments and also include cosmetic products - Wrinkles – Dryness - Sensitivity - redness in the skin - Pigmentation, see DEPFENHART ET AL. para [0115]-[0124])).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 16, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data includes image data of skin of the patient (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an arca of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 17, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the expert inference engine is configured to apply a machine learning classification model to the image data for determining skin features of the patient (see DEPFENHART ET AL. para [0052]-[0060], comprise databases which may include a plurality of weighting tables; and a set of instructions directed to at least one of a plurality of predictive equations for scoring a skin status quo code, a intrinsic code, a cosmetic code, a second unique code or a set of instructions to utilize a selection of the codes to make a cosmetic recommendation, see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 18, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data indicates a skin type of the patient, wherein the expert inference engine is configured to determine the settings based on the skin type (see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 19, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the skin type is a Fitzpatrick skin type (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], In Fitzpatrick Type V and VI, this see DEPFENHART ET AL. parameter would be described by taking an image using the VISIA system (or similar) to visualize inherent redness masked by melanin, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 20, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the Fitzpatrick skin type has a scale ranging from Type 1 to Type 6 (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], In Fitzpatrick Type V and VI, this see DEPFENHART ET AL. parameter would be described by taking an image using the VISIAᵀ system (or similar) to visualize inherent redness masked by melanin, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 21, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data indicates a redness of the skin of the patient, wherein the expert inference engine is configured to determine the settings based on the indicated redness (evaluation criteria and scale of scores for the skin characteristic of sensitivity, corresponding to specific see DEPFENHART ET AL. parameters (50) is illustrated in FIG. 5A. The presentation of visible inflammation and redness in the skin have associated scale of scores of 1 (51) to 5 (55). Wherein a score of 1 is none or barely perceivable redness, to a score of 5 being representative of permanent red patches, a skin that flushes easily, with significant number of broken capillaries, raised scaly patches or bumps. A common area in which this is observed is the nose and cheeks in zone 2 (22). Telangiectasias or broken capillaries contribute towards a high scoring in this area. Flushed cheeks, scaling and fine bumps are common indicators of inherent sensitivity, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 22, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the redness is indicated by a Kesty Redness scale (evaluation criteria and scale of scores for the skin characteristic of sensitivity, corresponding to specific see DEPFENHART ET AL. parameters (50) is illustrated in FIG. 5A. The presentation of visible inflammation and redness in the skin have associated scale of scores of 1 (51) to 5 (55). Wherein a score of 1 is none or barely perceivable redness, to a score of 5 being representative of permanent red patches, a skin that flushes easily, with significant number of broken capillaries, raised scaly patches or bumps. A common area in which this is observed is the nose and cheeks in zone 2 (22). Telangiectasias or broken capillaries contribute towards a high scoring in this arca. Flushed checks, scaling and fine bumps are common indicators of inherent sensitivity, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 23, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the Kesty Redness scale ranges from 0 - 4, wherein 0 indicates clear, 1 indicates almost clear, 2 indicates mild, 3 indicates moderate, and 4 indicates severe (evaluation criteria and scale of scores for the skin characteristic of sensitivity, corresponding to specific see DEPFENHART ET AL. parameters (50) is illustrated in FIG. 5A. The presentation of visible inflammation and redness in the skin have associated scale of scores of 1 (51) to 5 (55). Wherein a score of 1 is none or barely perceivable redness, to a score of 5 being representative of permanent red patches, a skin that flushes easily, with significant number of broken capillaries, raised scaly patches or bumps. A common area in which this is observed is the nose and cheeks in zone 2 (22). Telangiectasias or broken capillaries contribute towards a high scoring in this area. Flushed cheeks, scaling and fine bumps are common indicators of inherent sensitivity, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 24, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data comprises an indication of wrinkles of the skin of the patient, wherein the expert inference engine is configured to determine the settings based on the indication of wrinkles (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 25, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the redness is indicated by a Glogau Wrinkle scale and/ or a Fitzpatrick Wrinkle Severity scale (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], In Fitzpatrick Type V and VI, this see DEPFENHART ET AL. parameter would be described by taking an image using the VISIA™ system (or similar) to visualize inherent redness masked by melanin. Alternatively, it would be scored by unevenness of skin tone, not to be confused with the presence of pigmentation each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 26, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the Glogau Wrinkle scale ranges from Type 1 to Type 4, and wherein the Fitzpatrick Wrinkle Severity scale ranges from 1 - 9, wherein 1 indicates least wrinkles, and 9 indicates most wrinkles (Wrinkle severity has been quantified by a number of systems including Hamilton's Classification, Glogau's classification and Fitzpatrick's classification. It is understood that many wrinkle severity scales have been developed to reproducibly classify wrinkle severity and improvement after professional treatment, see DEPFENHART ET AL. para [0018], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 27, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data includes image data of skin of the patient, wherein the expert inference engine is configured to use a machine learning classification model to classify the skin of the patient based on the image data, and wherein the expert inference engine is configured to determine the settings based on the classification of the skin of the patient (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an area of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060], comprise databases which may include a plurality of weighting tables; and a set of instructions directed to at least one of a plurality of predictive equations for scoring a skin status quo code, an intrinsic code, a cosmetic code, a second unique code or a set of instructions to utilize a selection of the codes to make a cosmetic recommendation, see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 29, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the received data includes image data of skin of the patient, wherein the expert inference engine is configured to use a multi-label machine learning classification model trained to use the image data to predict skin features (The first input interface may be adapted to receive a direct data input, data derived from analysis of a photographic image or video images of a zone or an area of a person's body in respect of at least one of a plurality of skin characteristics, see DEPFENHART ET AL. para [0052]-[0060], comprise databases which may include a plurality of weighting tables; and a set of instructions directed to at least one of a plurality of predictive equations for scoring a skin status quo code, an intrinsic code, a cosmetic code, a second unique code or a set of instructions to utilize a selection of the codes to make a cosmetic recommendation, see DEPFENHART ET AL. para [0074]-[0082], see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 30, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the skin features are classified according to Fitzpatrick skin type, Kesty Redness, Kesty Pigmentation, Glogau Wrinkle Scale, and/or Fitzpatrick Wrinkle Severity Scale (see DEPFENHART ET AL. para [0052]-[0060], see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
As per claim 31, DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. disclose a system wherein the expert inference engine is configured to apply a machine learning classification model to the data for generating information that explains which regions of the skin of the patient were used for determining skin characteristics, and wherein the user interface is configured to present the generated information (utilizing the skin status quo code of the method - determining the at least one predetermined skin characteristic that may benefit from a cosmetic intervention; and recommending at least one cosmetic intervention to affect the predetermined skin characteristic, see DEPFENHART ET AL. para [0037]-[0046], see DEPFENHART ET AL. para [0052]-[0060], see DEPFENHART ET AL. para [0074]-[0082], each zone is analyzed for four skin characteristics (Wrinkles, Sensitivity, Pigmentation and Dehydration, or WSPD) on a scale of 1-5, where 1 is where the skin characteristic is insignificantly affected and 5 is severely affected, see DEPFENHART ET AL. para [0135]-[0145], The recommendation module is further capable of executing instructions to prepare recommendations of specific cosmetic code-based products and preparing and processing an output to an end user which may be the individual subject or an aesthetic practitioner, see DEPFENHART ET AL. para [0200]-[0210]).
The obviousness of combining the teachings of DEPFENHART et al. and ARAÚJO MARTINS VILAÇA et al. are discussed in the rejection of claim 13, and incorporated herein.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Pub. No.: US 20160027339 A1; Disclosed are various embodiments for providing dermatology-specific training to primary care providers. Primary care providers may register on the system and request access to various dermatology training materials. The primary care provider may be provided with the requested dermatology training materials when the primary care provider has a valid account. Payment may be required before a primary care provider can access the dermatology training materials.
Pub. No.: US 20160027339 A1; The medium includes instructions to implement dermatology training materials (133) that are divided into modules (121). Each of the modules is directed toward training primary care providers in diagnosing and treating a specific skin condition. An access to the training materials is restricted based on whether a user (127) has an active subscription. The modules are searched based on at least one criterion obtained from the user regarding an undiagnosed symptom. The rendering of a user interface is caused and the interface has search results from modules that meet criteria.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWARD B WINSTON III whose telephone number is (571)270-7780. The examiner can normally be reached M-F 1030 to 1830.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/E.B.W/Examiner, Art Unit 3683
/ROBERT W MORGAN/Supervisory Patent Examiner, Art Unit 3683