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 .
DETAILED ACTION
This action is responsive to the RCE filed 4/15/2026.
This action is made Non-Final.
Claims 1, 4-8, 10, 12-18 are pending in the case. Claims 1, 14, and 15 are independent claims.
Response to Arguments
Applicant’s arguments with respect to the pending claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Applicant is directed to the updated rejection of the claims wherein the Examiner articulates how the new combination of references teach every feature of the amended claims.
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.
Claim(s) 1, 7, 12, 14, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Naumovets (USPUB 20230121899 A1 filed Oct. 6, 2022, which claims priority to U.S. Prov. App. No: 63/256,891 filed Oct. 18, 2021) in view of Sager (USPUB 2009319068 A1 from IDS filed 3/30/3023) and further in view of Saphier (USPUB 20210321872 A1).
Claim 1:
Naumovets discloses A recognition method for a dental object (100-1), comprising the steps: providing (S101) a digital dental object (100-1) in a coordinate system describing a shape of the dental object (100-2) to be manufactured (0007-8: a method for automatic registration of dental image data may include receiving three-dimensional intraoral surface scan data of a dentition of a patient... at least one of the first set of descriptors and the second set of descriptors may include one or more descriptors characterizing curvature of the tooth crown surfaces); wherein a number of points on the surface of the digital dental object (100-1) is detected; wherein the points on the surface of the digital dental object (100-1) are randomly selected (0050: descriptors may be generated for a set of random points on the tooth crown surfaces, or descriptors may be generated at predetermined set of points on the tooth crown surfaces (e.g., in a grid pattern, such as in a triangular grid or rectangular grid). Additionally or alternatively, in some variations more descriptors may be generated in general regions on the tooth crown surfaces that may be anticipated to have more variance in curvature).
Though Naumovets discusses the digitized surfaces of the patient's dentition obtained from the intraoral surface scan may be used to create one or more patient-customized orthodontic appliances (0036), Naumovets, by itself, does not seem to completely teach automatically assigning (S102) a class to the digital dental object (100-1) to provide the type of the dental object, on the shape by a self-learning algorithm; wherein a manufacturing method is assigned to the digital dental object (100-1) based on the assigned class in which the type of the dental object belongs; and wherein the dental object (100-2) is produced by the manufacturing method.
The Examiner maintains that these features were previously well-known as taught by Saphier.
Saphier teaches automatically assigning (S102) a class to the digital dental object (100-1) to provide the type of the dental object, on the shape by a self-learning algorithm; wherein a manufacturing method is assigned to the digital dental object (100-1) based on the assigned class in which the type of the dental object belongs; and wherein the dental object (100-2) is produced by the manufacturing method (0043, 0045, 0349-350: receiving one or more intraoral scans of a patient's oral cavity; processing an input comprising data from the one or more intraoral scans using a trained machine learning model that has been trained to classify dental sites represented in intraoral scans, wherein the trained machine learning model generates an output comprising one or more dental classification, the one or more dental classification comprising an indication as to whether or not the one or more intraoral scans comprise a depiction of one or more types of restorative dental object; determining, based on the dental classification output by the trained machine learning model, that the one or more intraoral scans depict a restorative dental object... the one or more types of restorative dental object comprise a preparation, a scan body and a dental implant, and wherein the one or more dental classification comprises a preparation classification, a scan body classification and a dental implant classification... For example, separate ML models may be trained to determine a dental lab, a type of dental prosthetic, a material for a dental prosthetic, a color for a dental prosthetic, and so on... Case type classification—this can include determining whether orthodontic treatment and/or restorative treatment will be performed for a patient based on intraoral scans, sets of intraoral scans, 3D surfaces generated from multiple intraoral scans, 3D models generated from multiple intraoral scans, and so on).
Naumovets and Saphier are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Saphier before him or her, to combine the teachings of Naumovets and Saphier. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Saphier to obtain the invention as specified in the instant claim(s).
Claim 7:
Naumovets teaches wherein a digital reference object is assigned to the digital dental object (100-1) based on the assigned class (0009: determining the best-fit registration transform may include generating one or more registration transform candidates based on matching descriptors from the first and second sets of descriptors. One or more of the registration transform candidates may be generated based on a voting scheme such as a Hough transform. Furthermore, determining the best-fit registration transform may include generating one or more refined registration candidates by applying an iterative local registration procedure to the one or more registration transform candidates. Various suitable techniques to generate the refined registration candidate(s) may be used, including, for example, an iterative closest point to plane algorithm or an iterative closest point to point algorithm. Additionally or alternatively, in some variations, determining the best-fit registration transform may include generating a surface proximity measure associated with each of the one or more refined registration candidates, and identifying the refined registration transform candidate associated with a lowest surface proximity measure. In some variations, the best-fit registration transform may be determined by generating a surface proximity measure associated with each of the registration transform candidates).
Claim 12:
Naumovets teaches wherein the manufacturing method is an additive or subtractive manufacturing method (0075: 3D printing is discussed).
Claim 14:
Naumovets teaches A manufacturing apparatus (200) for a dental object (100-2), which is adapted to perform the recognition method according to claim 1 (0036).
Claim 15:
Naumovets teaches A computer program product comprising program code which is stored on a non-transitory machine-readable medium comprising computer instructions executable by a processor, which computer instructions cause the processor to perform the method according to claim 1 (0079).
Claim(s) 4-6, 8, 10, 13, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Naumovets (USPUB 20230121899 A1 filed Oct. 6, 2022, which claims priority to U.S. Prov. App. No: 63/256,891 filed Oct. 18, 2021) in view of Saphier (USPUB 20210321872 A1) and further in view of Sager (USPUB 2009319068 A1 from IDS filed 3/30/3023).
Claim 4:
Naumovets, by itself, does not seem to completely teach wherein coordinates of the detected points form an input for an artificial neural network (109).
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein coordinates of the detected points form an input for an artificial neural network (109) (0042: Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations. For example, design libraries of specific sizes and shapes for replacement teeth are continuously updated with data regarding the specific components that are designed and manufactured. This allows the system of the instant invention to capture and utilize trends of tooth numbers of missing teeth and teeth that are heavily worked upon to update the library of shapes and sizes that will be utilized in designing components).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 5:
Naumovets, by itself, does not seem to completely teach wherein the artificial neural network (109) has been trained by a plurality of training data sets.
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein the artificial neural network (109) has been trained by a plurality of training datasets (0042: Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations. For example, design libraries of specific sizes and shapes for replacement teeth are continuously updated with data regarding the specific components that are designed and manufactured. This allows the system of the instant invention to capture and utilize trends of tooth numbers of missing teeth and teeth that are heavily worked upon to update the library of shapes and sizes that will be utilized in designing components).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 6:
Naumovets, by itself, does not seem to completely teach wherein the class is output by the artificial neural network (109).
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein the class is output by the artificial neural network (109) (0008, 0042, 0046 and 0052: A principal object of the instant invention is to provide a system for simultaneously or mechanico-sequentially, designing and/or fabricating custom dental crown and bridge coping/infrastructures (Cores) and one or more other companion/collateral pieces (such as an implant abutment or crown mold) to reduce the amount of labor, time and/or materials. The process is accomplished by integrating, sharing and interpreting stored CAD/CAM digital job information, dental design and algorithms, CNC and CAM programs and advanced data warehousing and adaptive learning to achieve optimized custom milling results... The manufacturing system of the instant invention converges technologies such as scanning input, CAD design and CAM manufacturing together in an automated, centrally controlled system to allow for integrated, simultaneous manufacturing of two or more pieces of a dental restoration. The central control allows for adaptive learning by the system as information is exchanged between the CAD and CAM phases. For example, if a piece is designed in the CAD process that cannot physically be manufactured by the CAM equipment, the central control system will update (in addition to routine software updates coming from a program designer) the design file or database (or libraries) of the CAD system in real time to prevent the CAD system from making the same or similar design error in the future. As another example, the central processor can utilize prior design and manufacturing information to narrow predetermined design parameters. For example, after multiple design and manufacturing processes are completed, it may be learned that the diameter of stock material for a component such as a crown should be changed, or that one of multiple diameters of stock material is not necessary, due to the fact that all pieces end up being made of certain dimensions. Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations... the deconstructive manufacturing method begins with the purchase of the metal portion of the abutment from a manufacturer. The abutment analog is located in a model of the patient's mouth and the metal portion (analog) of the abutment, which is located in the model, is scanned. The data from the scan is then utilized to manufacture the ceramic portion of the abutment and the Core that fits around the ceramic portion of the abutment... the model is scanned and the shape and orientation of the final crown is determined or visualized by design software of the instant invention. The thickness for the crown is subtracted or deconstructed from the final shape of the substructure. First the thickness for the crown is subtracted from the final shape of the crown by the design software to determine the shape and orientation of the Core. The thickness of the Core (coping/infrastructure) is then subtracted to form the shape and orientation of the abutment. In one such an embodiment, the part of the final shape of the restoration that is subtracted is determined to maximize the aesthetic appearance of the final restoration by concealing the substructure. In one such embodiment, the software constructs a "mesh framework of point clusters" that are external to (or in addition to) the point clusters established by the scan of the original piece that is being restored (or scan of a model of the piece to establish the desired external appearance of the restoration). These point clusters are used to construct an image of a "concentric" substructure (concentric to the original piece) for the restoration. The operator then embellishes or diminishes certain key areas, after rendering of the substructure image, to design the final substructure shape. Once the basic, overall shape has been rendered, the computer then knows in 3d, through the point clusters, where the operator is working, allowing the operator to easily take away portions of the image to result in a final image for the substructure).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 8:
Naumovets, by itself, does not seem to completely teach wherein the digital dental object (100-1) is transformed based on the assigned class and/or the reference object in the coordinate system.
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein the digital dental object (100-1) is transformed based on the assigned class and/or the reference object in the coordinate system (0008, 0042, 0046 and 0052: A principal object of the instant invention is to provide a system for simultaneously or mechanico-sequentially, designing and/or fabricating custom dental crown and bridge coping/infrastructures (Cores) and one or more other companion/collateral pieces (such as an implant abutment or crown mold) to reduce the amount of labor, time and/or materials. The process is accomplished by integrating, sharing and interpreting stored CAD/CAM digital job information, dental design and algorithms, CNC and CAM programs and advanced data warehousing and adaptive learning to achieve optimized custom milling results... The manufacturing system of the instant invention converges technologies such as scanning input, CAD design and CAM manufacturing together in an automated, centrally controlled system to allow for integrated, simultaneous manufacturing of two or more pieces of a dental restoration. The central control allows for adaptive learning by the system as information is exchanged between the CAD and CAM phases. For example, if a piece is designed in the CAD process that cannot physically be manufactured by the CAM equipment, the central control system will update (in addition to routine software updates coming from a program designer) the design file or database (or libraries) of the CAD system in real time to prevent the CAD system from making the same or similar design error in the future. As another example, the central processor can utilize prior design and manufacturing information to narrow predetermined design parameters. For example, after multiple design and manufacturing processes are completed, it may be learned that the diameter of stock material for a component such as a crown should be changed, or that one of multiple diameters of stock material is not necessary, due to the fact that all pieces end up being made of certain dimensions. Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations... the deconstructive manufacturing method begins with the purchase of the metal portion of the abutment from a manufacturer. The abutment analog is located in a model of the patient's mouth and the metal portion (analog) of the abutment, which is located in the model, is scanned. The data from the scan is then utilized to manufacture the ceramic portion of the abutment and the Core that fits around the ceramic portion of the abutment... the model is scanned and the shape and orientation of the final crown is determined or visualized by design software of the instant invention. The thickness for the crown is subtracted or deconstructed from the final shape of the substructure. First the thickness for the crown is subtracted from the final shape of the crown by the design software to determine the shape and orientation of the Core. The thickness of the Core (coping/infrastructure) is then subtracted to form the shape and orientation of the abutment. In one such an embodiment, the part of the final shape of the restoration that is subtracted is determined to maximize the aesthetic appearance of the final restoration by concealing the substructure. In one such embodiment, the software constructs a "mesh framework of point clusters" that are external to (or in addition to) the point clusters established by the scan of the original piece that is being restored (or scan of a model of the piece to establish the desired external appearance of the restoration). These point clusters are used to construct an image of a "concentric" substructure (concentric to the original piece) for the restoration. The operator then embellishes or diminishes certain key areas, after rendering of the substructure image, to design the final substructure shape. Once the basic, overall shape has been rendered, the computer then knows in 3d, through the point clusters, where the operator is working, allowing the operator to easily take away portions of the image to result in a final image for the substructure).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 10:
Naumovets, by itself, does not seem to completely teach wherein further spatial structures are added to the digital dental object (100-1) based on the assigned manufacturing method.
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein further spatial structures are added to the digital dental object (100-1) based on the assigned manufacturing method (0008, 0042, 0046 and 0052: A principal object of the instant invention is to provide a system for simultaneously or mechanico-sequentially, designing and/or fabricating custom dental crown and bridge coping/infrastructures (Cores) and one or more other companion/collateral pieces (such as an implant abutment or crown mold) to reduce the amount of labor, time and/or materials. The process is accomplished by integrating, sharing and interpreting stored CAD/CAM digital job information, dental design and algorithms, CNC and CAM programs and advanced data warehousing and adaptive learning to achieve optimized custom milling results... The manufacturing system of the instant invention converges technologies such as scanning input, CAD design and CAM manufacturing together in an automated, centrally controlled system to allow for integrated, simultaneous manufacturing of two or more pieces of a dental restoration. The central control allows for adaptive learning by the system as information is exchanged between the CAD and CAM phases. For example, if a piece is designed in the CAD process that cannot physically be manufactured by the CAM equipment, the central control system will update (in addition to routine software updates coming from a program designer) the design file or database (or libraries) of the CAD system in real time to prevent the CAD system from making the same or similar design error in the future. As another example, the central processor can utilize prior design and manufacturing information to narrow predetermined design parameters. For example, after multiple design and manufacturing processes are completed, it may be learned that the diameter of stock material for a component such as a crown should be changed, or that one of multiple diameters of stock material is not necessary, due to the fact that all pieces end up being made of certain dimensions. Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations... the deconstructive manufacturing method begins with the purchase of the metal portion of the abutment from a manufacturer. The abutment analog is located in a model of the patient's mouth and the metal portion (analog) of the abutment, which is located in the model, is scanned. The data from the scan is then utilized to manufacture the ceramic portion of the abutment and the Core that fits around the ceramic portion of the abutment... the model is scanned and the shape and orientation of the final crown is determined or visualized by design software of the instant invention. The thickness for the crown is subtracted or deconstructed from the final shape of the substructure. First the thickness for the crown is subtracted from the final shape of the crown by the design software to determine the shape and orientation of the Core. The thickness of the Core (coping/infrastructure) is then subtracted to form the shape and orientation of the abutment. In one such an embodiment, the part of the final shape of the restoration that is subtracted is determined to maximize the aesthetic appearance of the final restoration by concealing the substructure. In one such embodiment, the software constructs a "mesh framework of point clusters" that are external to (or in addition to) the point clusters established by the scan of the original piece that is being restored (or scan of a model of the piece to establish the desired external appearance of the restoration). These point clusters are used to construct an image of a "concentric" substructure (concentric to the original piece) for the restoration. The operator then embellishes or diminishes certain key areas, after rendering of the substructure image, to design the final substructure shape. Once the basic, overall shape has been rendered, the computer then knows in 3d, through the point clusters, where the operator is working, allowing the operator to easily take away portions of the image to result in a final image for the substructure).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to mass produce dental hardware, as taught by Sager.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 13:
Naumovets, by itself, does not seem to completely teach wherein a correctness of the assignment is checked by geometric features of the digital dental object (100-1).
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein a correctness of the assignment is checked by geometric features of the digital dental object (100-1) (0042: The central control allows for adaptive learning by the system as information is exchanged between the CAD and CAM phases. For example, if a piece is designed in the CAD process that cannot physically be manufactured by the CAM equipment, the central control system will update (in addition to routine software updates coming from a program designer) the design file or database (or libraries) of the CAD system in real time to prevent the CAD system from making the same or similar design error in the future).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to ensure the most accurate dental hardware is manufactured.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim 16:
Naumovets, by itself, does not seem to completely teach wherein new classification data sets (101) are classified based on similarity to the plurality of the training data sets.
The Examiner maintains that these features were previously well-known as taught by Sager.
Sager teaches wherein new classification data sets (101) are classified based on similarity to the plurality of the training data sets (0042: The central control allows for adaptive learning by the system as information is exchanged between the CAD and CAM phases. For example, if a piece is designed in the CAD process that cannot physically be manufactured by the CAM equipment, the central control system will update (in addition to routine software updates coming from a program designer) the design file or database (or libraries) of the CAD system in real time to prevent the CAD system from making the same or similar design error in the future. As another example, the central processor can utilize prior design and manufacturing information to narrow predetermined design parameters. For example, after multiple design and manufacturing processes are completed, it may be learned that the diameter of stock material for a component such as a crown should be changed, or that one of multiple diameters of stock material is not necessary, due to the fact that all pieces end up being made of certain dimensions. Software control algorithms of the central control system continuously monitor the CAD and CAM phases, actions taken in those phases, evaluates design parameters and stores design parameters in a continuously updated database, to allow for the adaptive learning discussed above. For example, one control algorithm is programmed with or accesses data regarding the diameters of rod stock available for manufacturing certain pieces. The control algorithm continuously accesses and monitors data regarding actual components that are designed and manufactured by the central control system, and evaluates that data in real time to make a determination as to the proper diameter of material to be used to make the next piece that is being designed and/or manufactured. Other algorithms monitor and update libraries of data regarding preferred component designs for specific situations. For example, design libraries of specific sizes and shapes for replacement teeth are continuously updated with data regarding the specific components that are designed and manufactured. This allows the system of the instant invention to capture and utilize trends of tooth numbers of missing teeth and teeth that are heavily worked upon to update the library of shapes and sizes that will be utilized in designing components through the instant invention).
Naumovets and Sager are analogous art because they are from the same problem-solving area, manufacturing dental hardware.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Sager before him or her, to combine the teachings of Naumovets and Sager. The rationale for doing so would have been to ensure the most accurate dental hardware is manufactured.
Therefore, it would have been obvious to combine Naumovets and Sager to obtain the invention as specified in the instant claim(s).
Claim(s) 17 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Naumovets (USPUB 20230121899 A1 filed Oct. 6, 2022, which claims priority to U.S. Prov. App. No: 63/256,891 filed Oct. 18, 2021) in view of Saphier (USPUB 20210321872 A1) and Sager (USPUB 2009319068 A1 from IDS filed 3/30/3023) and further in view of Gopalan (USPAT 11151472 B2).
Claim 17:
Naumovets in view of Saphier and Sager teach every feature of claim 16.
Naumovets, by itself, does not seem to completely teach wherein the new classification data sets (101) are classified using a nonparametric method.
The Examiner maintains that these features were previously well-known as taught by Gopalan.
Gopalan teaches wherein the new classification data sets (101) are classified using a nonparametric method (Col 2 ln 52-62: the operations of the present disclosure may include computing a data distribution of the training data on which the machine learning model (and/or MLA) is first trained. Any parametric or non-parametric distribution can be used, such as Gaussian, Laplacian, Parzen window, etc. Next, the machine learning model may be deployed to process a stream of new data. For instance, the stream of new data may be segmented into blocks, time windows, etc., and applied to the machine learning model to perform a service, e.g., a classification, a prediction, etc).
Naumovets and Gopalan are analogous art because they are from the same problem-solving area, utilizing trained data models to assist in decision making.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Gopalan before him or her, to combine the teachings of Naumovets and Gopalan. The rationale for doing so would have been to ensure the most accurate dental hardware is manufactured.
Therefore, it would have been obvious to combine Naumovets and Gopalan to obtain the invention as specified in the instant claim(s).
Claim 18:
Naumovets in view of Saphier and Sager teach every feature of claim 16.
Naumovets, by itself, does not seem to completely teach wherein the new classification data sets (101) are classified using a linear support vector machine or Gaussian method.
The Examiner maintains that these features were previously well-known as taught by Gopalan.
Gopalan teaches wherein the new classification data sets (101) are classified using a linear support vector machine or Gaussian method (Col 2 ln 52-62: the operations of the present disclosure may include computing a data distribution of the training data on which the machine learning model (and/or MLA) is first trained. Any parametric or non-parametric distribution can be used, such as Gaussian, Laplacian, Parzen window, etc. Next, the machine learning model may be deployed to process a stream of new data. For instance, the stream of new data may be segmented into blocks, time windows, etc., and applied to the machine learning model to perform a service, e.g., a classification, a prediction, etc).
Naumovets and Gopalan are analogous art because they are from the same problem-solving area, utilizing trained data models to assist in decision making.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Naumovets and Gopalan before him or her, to combine the teachings of Naumovets and Gopalan. The rationale for doing so would have been to ensure the most accurate dental hardware is manufactured.
Therefore, it would have been obvious to combine Naumovets and Gopalan to obtain the invention as specified in the instant claim(s).
Note
The Examiner cites particular columns, line numbers and/or paragraph numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. See MPEP 2123.
Note
The Examiner cites particular columns, line numbers and/or paragraph numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. See MPEP 2123.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is listed in the attached PTOL-892 form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED-IBRAHIM ZUBERI whose telephone number is (571)270-7761. The examiner can normally be reached on M-Th 8-6 Fri: 7-12/OFF.
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, Steph Hong can be reached on (571) 272-4124. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMED H ZUBERI/Primary Examiner, Art Unit 2178
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