DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/03/2026 has been entered.
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 .
Response to Amendment
Claims 1, 17, and 23 have incorrect claim status identifiers.
Claims 4, 11, and 12 have a claim interpretation.
In light of the amendments, claim 22 is rejected under 35 U.S.C. 112(a).
In light of the amendments, claim 22 is rejected under 35 U.S.C. 112(b).
In light of the amendments, the claims are rejected under 35 U.S.C. 101.
In light of the amendments, the claims are rejected under 35 U.S.C. 103.
Notice to Applicant
In the amendments dated 06/30/2026 and 08/03/2026, the following has occurred: claims 1, 17, and 22 have been amended; claims 2-9, 11-16, and 18-21 remain unchanged; and claim 23 has been added.
Claims 1-9 and 11-23 are pending.
Effective Filing Date: 09/22/2023
Response to Arguments
35 U.S.C. 101 Rejections:
Step 2A, Prong One:
Applicant argues that the claims do not recite an abstract idea classified under certain methods of organizing human activity. Examiner however respectfully disagrees as the claims recite a method a human could perform to provide a treatment response prediction. Applicant argues that directing the claimed invention towards certain methods of organizing human activity would reduce any claimed algorithm to a method of organizing human activity. Examiner however respectfully disagrees with this hypothetical and cannot speak towards other claim sets apart from the present one. The present claim set does recite human activity.
As for claim 22, Applicant states that the abstract feature having no apparent meaning for a human user could not be something that is human activity. Examiner however respectfully disagrees in view of the 112 rejections given to claim 22. Data having no apparent meaning to a human can also provide meaning to a human; the lack of meaning can provide meaning to a person. Furthermore it is unclear what the data is.
Step 2A, Prong Two:
Applicant argues with respect to claim 4 and states that the claims are integrated into a practical application. Applicant states that providing a confidence measure equates to providing an improvement to automated medical image processing and diagnosis technologies. Examiner however respectfully disagrees. Initially, it is not described that the providing of a confidence score is an improvement within Applicant’s specification. Furthermore, providing a confidence score does not necessarily improve the treatment prediction response. Are the responses used to modify what response is provided? Or is this just extra information which is being provided without affecting anything?
35 U.S.C. 103 Rejections:
Applicant argues with respect to the amended language. This language was addressed with the Wolz et al. reference.
Status Identifiers for Claims
Under 37 C.F.R. 1.121 each amendment document must include status identifiers indicating the current status of each of the claims in the application. Examiner notes that the amendment document filed 08/03/2026 includes an incorrect status identifier for claims 1, 17, and 23. Claims 1 and 17 were amended in the after final claim set received on 06/30/2026 while claim 23 was added. The claim set of 06/30/2026 was not entered so the amendments to the claims would need to include those amendments as amendments in the claim set of 08/03/2026 if Applicant wants to include these amendments. While the current amendments have been entered for consideration, all further amendments to the claims must comply with the requirements set forth in 37 C.F.R. 1.121. Future such issues will accordingly result in a notice of non-compliance.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a certainty calculation module” in claim 4, “a data extraction module” in claim 11, and “an image analysis module” in claim 12.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. Paragraphs [0309] and [0310] describe that the structures for these modules are software executed using hardware components.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 22 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The limitation “no apparent meaning for a human user” is not supported in the specification to the extent that a treatment response prediction is being generated using this data, leading Examiner to question whether Applicant had possession over the claimed invention at the time of filing. If we do not know exactly what this data is then how can we base a treatment off of it?
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 22 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 22 recites “no apparent meaning for a human user” and this limitation is unclear as even a lack of meaning provides meaning for a user. Based on this lack of clarity in the claim, this claim has been deemed indefinite. Examiner is interpreting that these features are just data.
The term “apparent” in claim 22 is a relative term which renders the claim indefinite. The term “apparent” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “meaning” has been rendered indefinite in view of “apparent”.
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 1-9 and 11-23 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. Claims 1-9, 11-16, and 18-23 are drawn to a method and claim 17 is drawn to a system, each of which is within the four statutory categories. Claims 1-9 and 11-23 are further directed to an abstract idea on the grounds set out in detail below. As discussed below, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea (Step 1: YES).
Step 2A:
Prong One:
Claim 1 recites a computer-implemented method for providing a treatment response prediction for a patient suffering from a cancerous disease, the computer-implemented method comprising:
1) obtaining a whole slide image of the patient, the whole slide image showing a tissue sample relating to the cancerous disease;
2) obtaining, from a) a healthcare information system, a supplementary information associated with the patient, the supplementary information including at least one of
at least one additional whole slide image of the patient,
a radiological image,
a prior medical report of the patient, or
a medical guideline applicable for the patient;
3) generating a treatment response prediction for one or more treatment options by applying a prediction function to the whole slide image and the supplementary information; and
4) providing the treatment response prediction.
Claim 1 recites, in part, performing the steps of 2) obtaining a supplementary information associated with the patient, the supplementary information including at least one of at least one additional whole slide image of the patient, a radiological image, a prior medical report of the patient, or a medical guideline applicable for the patient, 3) generating a treatment response prediction for one or more treatment options by applying a prediction function to the whole slide image and the supplementary information, and 4) providing the treatment response prediction. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claim describes how one can make a prediction based on data. Independent claim 17 recites similar limitations and is also directed to an abstract idea under the same analysis.
Depending claims 2-16 and 18-23 include all of the limitations of claim 1, and therefore likewise incorporate the above described abstract idea. Depending claims 4-8, 10-11, 13, 20-21, 22 (based on the 112(b) interpretation), and 23. Additionally, the limitations of depending claims 2-3, 9, 12, 14-16, and 18-19 further specify elements from the claims from which they depend on without adding any additional steps. These additional limitations only further serve to limit the abstract idea. Thus, depending claims 2-16 and 18-23 are nonetheless directed towards fundamentally the same abstract idea as independent claim 1 (Step 2A (Prong One): YES).
Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of – using a) a healthcare information system and b) at least one processor (in claim 17) to perform the claimed steps.
Additionally, claims 1 and 17 include the additional element step of 1) “obtaining a whole slide image of the patient, the whole slide image showing a tissue sample relating to the cancerous disease”.
The a) healthcare information system and b) at least one processor in these steps are recited at a high-level of generality (i.e., as generic components performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using generic computer components (see: Applicant’s specification, paragraph [0312] where there is discussion of a general purpose computer executing functions, see MPEP 2106.05(f)).
The 1) “obtaining a whole slide image of the patient, the whole slide image showing a tissue sample relating to the cancerous disease” adds insignificant extra-solution activity to the abstract idea which amounts to mere data gathering, see MPEP 2106.05(g).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea (Step 2A (Prong Two): NO).
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a) a healthcare information system and b) at least one processor to perform the claimed steps and the additional element step of 1) “obtaining a whole slide image of the patient, the whole slide image showing a tissue sample relating to the cancerous disease” amounts to no more than insignificant extra-solution activity in the form of WURC activity (well-understood, routine, and conventional activity) and mere instructions to apply the exception using generic computer components that do not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. It should be noted that the claims do not include additional elements that amount to significantly more than the judicial exception because the Specification recites mere generic computer components, as discussed above that are being used to apply certain methods of organizing human activity steps. Specifically, MPEP 2106.05(d) and MPEP 2106.05(f) recite that the following limitations are not significantly more:
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)).
The additional element step of 1) “obtaining a whole slide image of the patient, the whole slide image showing a tissue sample relating to the cancerous disease” in these steps add insignificant extra-solution activity/pre-solution activity in the form of WURC activity to the abstract idea. The following is an example of a court decision demonstrating computer functions as well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II): Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec – similarly, the current invention receives whole image slide image data, and transmits the data to computing components over a network, for example the Internet.
Furthermore, the current invention provides a treatment response prediction utilizing a) a healthcare information system and b) at least one processor, thus these computing components are adding the words “apply it” with mere instructions to implement the abstract idea on a computer.
Mere instructions to apply an exception using generic computer components or insignificant extra-solution activity in the form of WURC activity cannot provide an inventive concept. The claims are not patent eligible (Step 2B: NO).
Claims 1-9 and 11-23 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-3, 12-14, 17-19, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2025/0285457 to McGinnis et al. in view of U.S. 2018/0190369 to Wolz et al.
As per claim 1, McGinnis et al. teaches a computer-implemented method for providing a treatment response prediction for a patient suffering from a cancerous disease, (see: paragraph [0004] where there is such a method) the computer-implemented method comprising:
--obtaining a whole slide image of the patient, (see: paragraph [0021] and 202 of FIG. 2A where there is receiving of a whole slide image of a patient) the whole slide image showing a tissue sample relating to the cancerous disease; (see: paragraph [0019] where there is a whole slide image showing tissue sample related to a cancerous disease)
--obtaining, from a healthcare information system, a supplementary information associated with the patient; (see: paragraph [0053] where there is obtaining of supplementary information in the form of annotations associated with the image)
--generating a treatment response prediction for one or more treatment options by applying a prediction function to the whole slide image; (see: 208 of FIG. 2A and paragraph [0032] where the diagnosis and treatment engine uses the composition profile to generate a prediction of a response to a treatment. Also see: paragraph [0030] where the composition profile includes data of the slide image) and
--providing the treatment response prediction (see: paragraphs [0019] – [0020] and 258 of FIG. 2B where there is providing of a prediction of a response to a treatment).
McGinnis et al. may not further, specifically teach:
1) --the supplementary information including at least one of
--at least one additional whole slide image of the patient,
--a radiological image,
--a prior medical report of the patient, or
--a medical guideline applicable for the patient;
2) --generating a treatment response prediction for one or more treatment options by applying a prediction function to the supplementary information.
Wolz et al. teaches:
1) --the supplementary information including at least one of
--at least one additional whole slide image of the patient,
--a radiological image,
--a prior medical report of the patient, (see: paragraphs [0011] and [0012] where there is collection of medical history information (supplementary information) for a patient) or
--a medical guideline applicable for the patient; and
2) --generating a treatment response prediction for one or more treatment options by applying a prediction function to the supplementary information (see: paragraphs [0011] and [0012] where there is collection of imaging data and medical history information (supplementary information) for a patient, and then there is a determination of a predicted treatment response by using the data with a model (prediction function)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute 1) the supplementary information including at least one of at least one additional whole slide image of the patient, a radiological image, a prior medical report of the patient, or a medical guideline applicable for the patient as taught by Wolz et al. for the supplementary information as disclosed by McGinnis et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, McGinnis et al. teaches of feeding supplementary information into a model thus one can replace that data with more data and achieve predictable results of training a model to be relevant for a patient. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
Furthermore, one of ordinary skill before the effective filing date of the claimed invention would have found it obvious to 2) generate a treatment response prediction for one or more treatment options by applying a prediction function to the supplementary information as taught by Wolz et al. in the method as taught by McGinnis et al. with the motivation(s) of determining adjustments to treatment (see: paragraph [0012] of Wolz et al.).
As per claim 2, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches wherein the one or more treatment options comprise at least one of:
--a radiotherapy treatment,
--an immunotherapy treatment, (see: paragraph [0019] where there is an immunotherapy treatment)
--a chemotherapy treatment, or
--a treatment by surgical intervention.
As per claim 3, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches wherein the treatment response prediction comprises at least one of:
--a predicted susceptibility of the cancerous disease to the one or more treatment options,
--a probability for a reoccurrence of the cancerous disease based on the one or more treatment options, or
--a predicted survival rate of the patient with the one or more treatment options (see: paragraph [0032] where the treatment response is based on a variety of clinical outcomes including overall survival).
As per claim 12, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches wherein the supplementary information includes radiology image data depicting a manifestation of the cancerous disease in a body of the patient (see: paragraph [0022] where there is an annotation of data that may depict a manifestation of a disease).
As per claim 13, McGinnis et al. and Wolz et al. in combination teaches the method of claim 12, see discussion of claim 12. McGinnis et al. further teaches:
--providing an image analysis module configured to extract a radiological observable from radiology image data; (see: paragraph [0025] where information is being extracted from an image, thus this extraction is being provided) and
--applying the image analysis module on the radiology image data to obtain the radiological observable, (see: paragraph [0025] where information is being extracted from an image, thus this extraction is being applied to the image) wherein
--the prediction function is further configured to derive the treatment response prediction additionally based on the radiological observable, (see: paragraph [0038] where the extracted image data is used for determining a treatment response prediction) and
--the generating the treatment response includes additionally applying the prediction function to the radiological observable (see: paragraph [0038] where the extracted image data is used for determining a treatment response prediction).
As per claim 14, McGinnis et al. and Wolz et al. in combination teaches the method of claim 13, see discussion of claim 13. McGinnis et al. further teaches wherein the radiological observable comprises at least one of:
--a tumor burden of the patient in the radiology image data, (see: paragraphs [0032] and [0040] where there is a determination of a disease burden)
--a visual characteristic of a lesion depicted in the radiology image data, or
--a temporal evolution of a lesion depicted in the radiology image data.
As per claim 17, claim 17 is similar to claim 1 and is therefore rejected in a similar manner to claim 1. McGinnis et al. further teaches a system for providing a treatment response prediction for a patient suffering from a cancerous disease, the system comprising:
--at least one processor (see: paragraph [0058] where there is such a processor).
As per claim 18, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches a non-transitory computer program product comprising program elements that induce a computing unit of a system to perform the method of claim 1, when the program elements are loaded into a memory of the computing unit (see: paragraph [0006] where there is a non-transitory medium where there are instructions in memory. The program is loaded into memory here).
As per claim 19, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by at least one processor of a system, cause the system to perform the method according to claim 1 (see: paragraph [0006] where there is a non-transitory medium where there are instructions in memory).
As per claim 22, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. McGinnis et al. further teaches wherein the generating the treatment response prediction includes
--extracting one or more features from whole slide images, the one or more features including one or more abstract feature having no apparent meaning for a human user, (see: paragraphs [0030] and [0031] where there is extraction of features from the image to get a composition profile. The limitation involving having no apparent user is being interpreted as just data based on the 112(b) rejection interpretation) and
--generating the treatment response prediction based on the one or more features. (see: 208 of FIG. 2A and paragraph [0032] where the diagnosis and treatment engine uses the composition profile to generate a prediction of a response to a treatment. Also see: paragraph [0030] where the composition profile includes data of the slide image).
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2025/0285457 to McGinnis et al. in view of U.S. 2018/0190369 to Wolz et al. as applied to claim 1, and further in view of U.S. 2023/0109108 to Banerjee et al.
As per claim 4, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. The combination may not further, specifically teaches:
1) --providing a certainty calculation module configured to output a certainty measure for a corresponding treatment response prediction, the certainty measure measuring a confidence of the corresponding treatment response prediction;
2) --applying the certainty calculation module to obtain a certainty measure for the treatment response prediction; and
3) --providing the certainty measure for the treatment response prediction.
Banerjee et al. teaches:
1) --providing a certainty calculation module configured to output a certainty measure for a corresponding treatment response prediction, (see: paragraph [0129] where there is providing of a module to output a certainty metric) the certainty measure measuring a confidence of the corresponding treatment response prediction; (see: paragraph [0129] where there is a measure of a confidence of a determination. The determination being related to a prediction response was taught in the independent claim rejection)
2) --applying the certainty calculation module to obtain a certainty measure for the treatment response prediction; (see: paragraph [0129] where the module for outputting the certainty metric is being applied) and
3) --providing the certainty measure for the treatment response prediction (see: paragraph [0129] where there is providing of a module to output a certainty metric)
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to 1) provide a certainty calculation module configured to output a certainty measure for a corresponding treatment response prediction, the certainty measure measuring a confidence of the corresponding treatment response prediction, 2) apply the certainty calculation module to obtain a certainty measure for the treatment response prediction, and 3) provide the certainty measure for the treatment response prediction as taught by Banerjee et al. in the method as taught by McGinnis et al. and Wolz et al. in combination with the motivation(s) of helping establish trust in the output (see: paragraph [0178] of Banerjee et al.).
As per claim 5, McGinnis et al., Wolz et al., and Banerjee et al. in combination teaches the method of claim 4, see discussion of claim 4. Banerjee et al. further teaches wherein the providing the certainty measure comprises:
--outputting the certainty measure together with the treatment response prediction to a user via a user interface (see: paragraph [0129] where there is outputting of a module to output a certainty metric).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 4, and incorporated herein.
Claims 6, 20-21, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2025/0285457 to McGinnis et al. in view of U.S. 2018/0190369 to Wolz et al. further in view of U.S. 2023/0109108 to Banerjee et al. as applied to claims 4-5, and further in view of U.S. 2019/0043619 to Vaughn et al.
As per claim 6, McGinnis et al., Wolz et al., and Banerjee et al. in combination teaches the method of claim 4, see discussion of claim 4. The combination may not further, specifically teach:
--determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; and
--in response to the treatment response prediction being inconclusive
--determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive.
Vaughn et al. teaches:
--determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; (see: paragraph [0185] where there is a determination of whether a prediction is conclusive or not. The prediction being related to a treatment response was taught in claim 1) and
--in response to the treatment response prediction being inconclusive
--determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive (see: paragraph [0185] where, in response to a determination of being inconclusive, there is a determination of which information is suited for rendering a conclusive prediction. The prediction being related to a treatment response and the usage of a whole slide image were taught in claim 1. More sophisticated models are being generated based on this additional information in paragraph [0189]. When determining that sophisticated models are applicable that means that there is a determination that additional data is available for using these sophisticated models).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine, based on the certainty measure, whether or not the treatment response prediction is conclusive and in response to the treatment response prediction being inconclusive determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive as taught by Vaughn et al. in the method as taught by McGinnis et al., Wolz et al., and Banerjee et al. in combination with the motivation(s) of improving the sensitivity and specificity for determinations (see: Abstract of Vaughn et al.).
As per claim 20, McGinnis et al., Wolz et al., and Banerjee et al. in combination teaches the method of claim 5, see discussion of claim 5. The combination may not further, specifically teach:
--determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; and
--in response to the treatment response prediction being inconclusive
--determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive.
Vaughn et al. teaches:
--determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; (see: paragraph [0185] where there is a determination of whether a prediction is conclusive or not. The prediction being related to a treatment response was taught in claim 1) and
--in response to the treatment response prediction being inconclusive
--determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive (see: paragraph [0185] where, in response to a determination of being inconclusive, there is a determination of which information is suited for rendering a conclusive prediction. The prediction being related to a treatment response and the usage of a whole slide image were taught in claim 1. More sophisticated models are being generated based on this additional information in paragraph [0189]. When determining that sophisticated models are applicable that means that there is a determination that additional data is available for using these sophisticated models).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine, based on the certainty measure, whether or not the treatment response prediction is conclusive and in response to the treatment response prediction being inconclusive determining a piece of information relating to the patient that is different than the whole slide image and which is suited for rendering the treatment response prediction conclusive as taught by Vaughn et al. in the method as taught by McGinnis et al., Wolz et al., and Banerjee et al. in combination with the motivation(s) of improving the sensitivity and specificity for determinations (see: Abstract of Vaughn et al.).
As per claim 21, McGinnis et al., Wolz et al., Banerjee et al., and Vaughn et al. in combination teaches the method of claim 6, see discussion of claim 6. Vladimirova et al. further teaches:
--retrieving the piece of information from the healthcare information system; (see: Abstract where there is reception of information from a system)
--processing the piece of information to provide an updated treatment response prediction; (see: Abstract where there is processing of this information to generate a prediction. Predictions can be performed over and over, thus this claim language describes a second prediction with this invention) and
--providing the updated treatment response prediction (see: Abstract where there is providing a prediction based on the information. Predictions can be performed over and over, thus this claim language describes a second prediction with this invention).
As per claim 23, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. The combination may not further, specifically teaches:
1) --obtaining a certainty measure for the treatment response prediction, the certainty measure measuring a confidence of the treatment response prediction;
2) --determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; and
3) --in response to the treatment response prediction being inconclusive, determining an additional piece of information based on a predictive impact of the additional piece of information, the additional piece of information relating to the patient being different from the whole slide image and being suited for rendering the treatment response prediction conclusive.
Banerjee et al. teaches:
1) --obtaining a certainty measure for the treatment response prediction, the certainty measure measuring a confidence of the treatment response prediction (see: paragraph [0129] where the module for outputting the certainty metric is being applied).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to 1) obtain a certainty measure for the treatment response prediction, the certainty measure measuring a confidence of the treatment response prediction as taught by Banerjee et al. in the method as taught by McGinnis et al. and Wolz et al. in combination with the motivation(s) of helping establish trust in the output (see: paragraph [0178] of Banerjee et al.).
Vaughn et al. teaches:
2) --determining, based on the certainty measure, whether or not the treatment response prediction is conclusive; (see: paragraph [0185] where there is a determination of whether a prediction is conclusive or not. The prediction being related to a treatment response was taught in claim 1) and
3) --in response to the treatment response prediction being inconclusive, determining an additional piece of information based on a predictive impact of the additional piece of information, the additional piece of information relating to the patient being different from the whole slide image and being suited for rendering the treatment response prediction conclusive (see: paragraph [0185] where, in response to a determination of being inconclusive, there is a determination of which information is suited for rendering a conclusive prediction. The prediction being related to a treatment response and the usage of a whole slide image were taught in claim 1. More sophisticated models are being generated based on this additional information in paragraph [0189]. When determining that sophisticated models are applicable that means that there is a determination that additional data is available for using these sophisticated models).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to 2) determine, based on the certainty measure, whether or not the treatment response prediction is conclusive and 3) in response to the treatment response prediction being inconclusive, determining an additional piece of information based on a predictive impact of the additional piece of information, the additional piece of information relating to the patient being different from the whole slide image and being suited for rendering the treatment response prediction conclusive as taught by Vaughn et al. in the method as taught by McGinnis et al., Wolz et al., and Banerjee et al. in combination with the motivation(s) of improving the sensitivity and specificity for determinations (see: Abstract of Vaughn et al.).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2025/0285457 to McGinnis et al. in view of U.S. 2018/0190369 to Wolz et al. as applied to claim 1, and further in view of U.S. 2024/0305588 to Chu et al.
As per claim 11, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. The combination may not further, specifically teach:
--providing a data extraction module configured to search an electronic medical record of the patient for the supplementary information, the data extraction module including a large language model, and wherein
--the obtaining of the supplementary information includes
--accessing the electronic medical record of the patient in the healthcare information system, and
--applying the data extraction module to the electronic medical record to obtain the supplementary information.
Chu et al. teaches:
--providing a data extraction module configured to search an electronic medical record of the patient for the supplementary information, (see: paragraph [0015] where there is extraction of data from an EMR) the data extraction module including a large language model, (see: paragraph [0021] where there is a LLM) and wherein
--the obtaining of the supplementary information includes
--accessing the electronic medical record of the patient in the healthcare information system, (see: paragraph [0015] where there is extraction of data from an EMR, thus there is accessing of an EMR) and
--applying the data extraction module to the electronic medical record to obtain the supplementary information (see: paragraph [0015] where there is extraction of data from an EMR, thus there is application of an extraction module ).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to provide a data extraction module configured to search an electronic medical record of the patient for the supplementary information, the data extraction module including a large language model, and wherein the obtaining of the supplementary information includes accessing the electronic medical record of the patient in the healthcare information system, and applying the data extraction module to the electronic medical record to obtain the supplementary information as taught by Chu et al. in the method as taught by McGinnis et al. and Wolz et al. in combination with the motivation(s) of providing information (see: paragraph [0015] of Chu et al.).
Claims 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2025/0285457 to McGinnis et al. in view of U.S. 2018/0190369 to Wolz et al. as applied to claim 1, and further in view of U.S. 2020/0384289 to Smith et al.
As per claim 15, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. The combination may not further, specifically teach wherein the one or more treatment options comprise at least two different radiotherapy treatment options, the at least two different radiotherapy treatment options differing in at least one of:
--a dose distribution,
--a dose threshold limit,
--a dose rate,
--a fractionation,
--a usage of proton/photon or electron radiation, or
--a usage of a co-planar or non-co-planar beam.
Smith et al. teaches:
--wherein the one or more treatment options comprise at least two different radiotherapy treatment options, the at least two different radiotherapy treatment options differing in at least one of:
--a dose distribution,
--a dose threshold limit,
--a dose rate, (see: paragraph [0081] where there is a dose rate)
--a fractionation, (see: paragraph [0079] where there is fractionation)
--a usage of proton/photon or electron radiation, or
--a usage of a co-planar or non-co-planar beam.
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein the one or more treatment options includes a radiotherapy treatment with a dose rate greater than 40 Gy/sec as taught by Smith et al. in the method as taught by McGinnis et al. and Wolz et al. in combination with the motivation(s) of being a type of treatment (see: paragraphs [0081] and [0083] of Smith et al.).
As per claim 16, McGinnis et al. and Wolz et al. in combination teaches the method of claim 1, see discussion of claim 1. The combination may not further, specifically teach wherein the one or more treatment options includes a radiotherapy treatment with a dose rate greater than 40 Gy/sec.
Smith et al. teaches:
--wherein the one or more treatment options includes a radiotherapy treatment with a dose rate greater than 40 Gy/sec (see: paragraph [0081] where there is a dose rate greater than 40 Gy/sec).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein the one or more treatment options includes a radiotherapy treatment with a dose rate greater than 40 Gy/sec as taught by Smith et al. in the method as taught by McGinnis et al. and Wolz et al. in combination with the motivation(s) of being a type of treatment (see: paragraphs [0081] and [0083] of Smith et al.).
Conclusion
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/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684
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