DETAILED ACTION
Status of Claims
This action is in reply to the application filed on 17 December, 2024.
Claims 1 - 20 are currently pending and have been examined.
The present application is a CIP of US Application No. 17/690,117, now US 12,176,108, which is a CIP of US Application No. 16/890,686, now US 11,289,206.
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 .
Claim Objections
Claims 3, 5, 6, 13, 15 and 16 are objected to because of the following informalities: Claims 3, 5, 6, 13, 15 and 16 recite “selecting” the curative habit pattern; however, the claims depend indirectly from Claim 1 and 11, which recite “generating” the curative habit pattern. The claims should use the same term Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1 - 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3 – 10, and 12 - 18 of U.S. Patent No. 12,176,108 B2, in view of Burd et al.: (US PGPUB 2021/0134433 A1). Although the pending independent claims are not identical to the issued claims, they are not patentably distinct from each other. In particular, issued Claims 1 and 10 recite all of the limitations in pending Claims 1 and 11, respectively, except for the following limitations:
wherein the curative habitual pattern contains a nutrition pattern containing a nutrition target for each eating occasion contained within the nutrition pattern.
The issued claims do not recite a particular type of curative habitual pattern; however, Burt does. Burt (@ Abstract, 0006, 0053, 0057, 0060, 0061) discloses a system and method for generating a dietary regimen that includes nutrition targets for each meal (i.e. eating occasion), based on user data. It would be obvious to modify the curative behavior patterns recited in the issued claims to include a nutrition pattern containing a nutrition target for each eating occasion, in order to treat a disorder.
With respect to Claims 2 and 12, Burt further discloses the following limitations:
wherein the user physiological history data is collected from a user questionnaire; (Burt 0035, 0046).
It would be obvious to modify the user physiological history data recited in the issued claims to specify that the data is collected from a user questionnaire. Examiner notes the questionnaire to collect physiological data is notoriously old and well-known.
The pending dependent Claims 5 - 10 and 15 – 20 are identical to issued dependent Claims 4 – 9 and 13 – 18, respectively. Claims 3, 4, 13 and 14 recite limitations that are identical to those found in issued Claims 1, 3, 10 and 12, however rearranged.
The table below shows the pending claims and their corresponding issued claims:
Pending Claims Issued Claims
1 1/Burt
2 Burt
3 1/3/Burt
4 1/Burt
5 4/Burt
6 5/Burt
7 6/Burt
8 7/Burt
9 8/Burt
10 9/Burt
11 10/Burt
12 Burt
13 10/12/Burt
14 10/Burt
15 13/Burt
16 14/Burt
17 15/Burt
18 16/Burt
19 17/Burt
20 18/Burt
Claims 1 - 20 are further rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 - 3, 7, 11 - 13 and 17 of U.S. Patent No. 11,289,206 B2, in view of Burd et al.: (US PGPUB 2021/0134433 A1). Although the pending independent claims are not identical to the issued claims, they are not patentably distinct from each other. In particular, issued Claims 1 and 10 recite all of the limitations in pending Claims 1 and 11, respectively, except for the following limitations:
wherein the curative habitual pattern contains a nutrition pattern containing a nutrition target for each eating occasion contained within the nutrition pattern.
The issued claims do not recite a particular type of curative habitual pattern; however, Burt does. Burt (@ Abstract, 0006, 0053, 0057, 0060, 0061) discloses a system and method for generating a dietary regimen that includes nutrition targets for each meal (i.e. eating occasion), based on user data. It would be obvious to modify the curative behavior patterns recited in the issued claims to include a nutrition pattern containing a nutrition target for each eating occasion, in order to treat a disorder.
With respect to Claims 2 and 12, Burt further discloses the following limitations:
wherein the user physiological history data is collected from a user questionnaire; (Burt 0035, 0046).
It would be obvious to modify the user physiological history data recited in the issued claims to specify that the data is collected from a user questionnaire. Examiner notes the questionnaire to collect physiological data is notoriously old and well-known.
The pending dependent Claims 8 - 10 and 18 – 20 are identical to issued dependent Claims 2, 3, 7, 12, 13 and 17, respectively. Claims 3 – 7 and 13 - 17 recite limitations that are identical to those found in issued Claim 1, however rearranged.
The table below shows the pending claims and their corresponding issued claims:
Pending Claims Issued Claims
1 1/Burt
2 Burt
3 - 7 1/Burt
8 7/Burt
9 2/Burt
10 3/Burt
11 11/Burt
12 Burt
13 - 17 11/Burt
18 17/Burt
19 12/Burt
20 13/Burt
Claim Rejections - 35 USC § 112
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.
Claims 3 and 13 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claims 3 and 13 recite: “wherein selecting the curative habitual pattern further comprises”. However, no selection is recited in the claims from which the claims depend. For purposes of this examination, Examiner assume that the claims recite “wherein generating the curative habitual pattern further comprises”. Appropriate correction is required.
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 - 20 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), and does not include additional elements that either: 1) integrate the abstract idea into a practical application, or 2) that provide an inventive concept – i.e. an element that amounts to significantly more than the abstract idea. The Claims are directed to an abstract idea because, when considered as a whole, the plain focus of the claims is on an abstract idea.
Claim 11 is representative. Claim 11 recites:
A method for constitutional analysis using objective functions, the method comprising:
generating a ranked list of diseases, wherein generating further comprises:
determining a plurality of disease impact score vectors associated with a plurality of diseases;
generating a first objective function of the impact score vectors; and
ranking the diseases according to optimization of the first objective function;
receiving, from a user, a plurality of user physiological history data, wherein the user physiological history data was collected by a wearable device;
identifying, as a function of a disease state classifier, a plurality of disease states associated with the plurality of user physiological history data;
matching at least a disease state of the plurality of disease states to the ranked list of diseases; and
generating a curative habitual pattern to alleviate the at least a disease state, wherein the curative habitual pattern contains a nutrition pattern containing a nutrition target for each eating occasion contained within the nutrition pattern.
Claim 1 recites a system that executes the steps of the method recited in Claim 11.
STEP 1
The claims are directed to a system and a method which are included in the statutory categories of invention.
STEP 2A PRONG ONE
The claims, as illustrated by Claim 11, recite limitations that encompass a first abstract idea including:
generating a ranked list of diseases, wherein generating further comprises: determining a plurality of disease impact score vectors associated with a plurality of diseases; generating a first objective function of the impact score vectors; and ranking the diseases according to optimization of the first objective function.
The claimed limitations encompass a first abstract idea within the mathematical formula or relationship grouping. The claims recite generating a ranked list of diseases according to optimization of a first objective function applied to disease impact score vectors. The specification discloses that disease impact score vectors may be obtained by direct input of an expert, or as statistics reported by health reporting agencies (CDC, NIH, etc.) which may be received by the system (0013). Ranked lists of diseases, received from others, is an insignificant extra-solution activity – i.e. data gathering. The objective function applied to the data is defined by the specification as “a mathematical function used by a computing device to score a quantitative element such as an impact score vector.” Optimizing is disclosed as a “mathematical solver” or an “optimization algorithm” that maximizes scores, or minimizes a loss function. The solver may be implemented as a third-party solver. As such, generating a ranked list of diseases encompasses applying known mathematical functions to the received data.
The claims, as illustrated by Claim 11, recite limitations that encompass a second abstract idea including:
receiving, from a user, a plurality of user physiological history data;
identifying a plurality of disease states associated with the plurality of user physiological history data;
matching at least a disease state of the plurality of disease states to the ranked list of diseases; and
generating a curative habitual pattern to alleviate the at least a disease state, wherein the curative habitual pattern contains a nutrition pattern containing a nutrition target for each eating occasion contained within the nutrition pattern.
The claimed limitations encompass a second abstract idea within the “mental process” grouping – concepts performed in the human mind including observation, evaluation, judgment and opinion. The claims recite identifying disease states based on user physiological history data; matching the disease state to the ranked list of diseases; and generating a curative habitual pattern to alleviate the disease state. Determining a user’s disease state, or making a diagnosis, is an ordinary mental process practiced routinely in medicine. Matching is disclosed in the specification as comparing labels of disease states which may share identical labels. Comparing labels is an ordinary mental process. A curative habit pattern is defined in the specification as “a set of regularly applied fitness, nutrition, and/or dietary actions, or any other pattern of behavioral habits” that may alleviate one of more disease states. The pattern is generated by forming a query using the disease state label; and intervention elements are thereby retrieved from a datastore. This simply look-up function may be performed mentally – i.e. referring to best practice guid3eline for the disease state.
Collecting and analyzing data and displaying the results is abstract, when it is performed using conventional computer and network technology. Collecting information is within the realm of abstract ideas; analyzing information by steps that people go through in their minds, or by mathematical algorithms are essentially mental processes within the abstract idea category; and merely presenting the results of abstract processes is abstract as an ancillary part of such collection and analysis. (Electric Power Group).
The specification discloses that disease impact scores may be obtained by direct input of an expert (0013). Alternately, statistics reported by health reporting agencies (CDC, NIH, etc.) and a statistical analysis of the reported data. Direct expert input of an impact score is inherently a mental process performed by the expert. Similarly, statistical analysis of data reported by the CDC or NIH, under the broadest reasonable interpretation of the claims, using well-known techniques as disclosed in the specification, is a process that, except for generic computer implementation steps, can be performed in the human mind. The recited vector may reasonably be construed as a “point” – i.e. the reported or input impact score itself. As a result, the recited objective function, and the ranking according to its optimization, may reasonably be construed as a mental recognition and judgement as to the disease with the highest impact score, for example by comparison. Receiving physiological data of a user and identifying a disease state associated with the data is an ordinary mental process routinely practiced in medicine – i.e. a disease state classifier is a mental process. For example, a doctor, upon receiving data indicating consistently high blood pressure over time, together with other routine diagnostic test results, may easily diagnose the user as having a disease state of hypertension. Matching this disease state to a list of diseases is a simple comparison of disease names. The recited curative habitual pattern to alleviate the disease state are described as well-known interventions – i.e. diet, sleep, exercise, meditation, consultation, etc. As above, the specification discloses that the curative impact score may be received by direct input of an expert (0043). Combining these well-known interventions to form a curative habitual pattern candidate is an ordinary mental process routinely practiced in medicine. For example, in the above example of a user with hypertension, a doctor may suggest interventions including a healthy diet, (less salt, fat, calories, etc.), weight loss, exercise, and in addition may prescribe medications, or some other combination of interventions. Using the scores assigned by experts to individual interventions, and calculating an aggregated score for a candidate pattern is a process that, except for generic computer implementation steps, can be performed in the human mind. As such, the claims recite an abstract idea within the mental process grouping.
STEP 2A PRONG TWO
The claims recite additional elements beyond those that encompass the abstract idea above including:
wherein the user physiological history data was collected by a wearable device;
a disease state classifier
However, these additional elements do not integrate the abstract idea into a practical application of that idea in accordance with MPEP 2106.05.
The wearable device is recited at a high level of generality such that it generally links the abstract idea to a particular technological environment. Receiving user physiological history data may further be construed as an extra-solution data gathering step. Nothing in the claim recites specific limitations directed to technological improvements. (see Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17 (Fed. Cir. 2014)). As such, the additional elements recited in the claim do not integrate the abstract diagnostic and intervention selection process into a practical application of that process.
STEP 2B
The additional elements identified above do not amount to significantly more than the abstract diagnostic and intervention selection process. Receiving user physiological data is a well-understood, routine and conventional computer function – i.e. receiving or transmitting data over a network as in Symantec, TLI, OIP and buySAFE; or electronic recordkeeping as in Alice and Ultramercial. Storing and retrieving information from memory is a routine and conventional computer function as in Versata and OIP Tech.
The additional structural elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generic computer structure (i.e. a computing device and datastore). Each of the above components are disclosed in the specification as being purely conventional and/or known in the industry. Because the specification describes these additional elements in general terms, without describing particulars, Examiner concludes that the claim limitations may be broadly, but reasonably construed, as reciting well-understood, routine and conventional computer components and techniques. The specification describes the elements in a manner that indicates that they are sufficiently well-known that the specification does not need to describe the particulars in order to satisfy U.S.C. 112. Considered as an ordered combination the limitations recited in the claims add nothing that is not already present when the steps are considered individually.
The dependent claims add additional features including:
those that merely serve to further narrow the abstract idea above such as:
further limiting collecting the physiological history data from a questionnaire (Claim 2);
further limiting the type of objective function; (Claims 9, 10);
those that recite additional abstract ideas such as:
calculating curative impact scores; (Math) selecting a curative habitual pattern; (Mental) (Claim 3);
generating and optimizing a second objective function; (Math) (Claim 3);
comparing vectors; selecting based on the comparison; (Claim 5, 6);
determining a likelihood of a plurality of disease states (Claim 7);
weighting elements in a list; (Claim 8);
those that recite well-understood, routine and conventional activity or computer functions such as:
receiving training data and training a machine learning model; (Claim 4);
The additional limitations recited in the dependent claims, in combination with those recited in the independent claims add nothing that integrates the abstract idea into a practical application, or that amounts to significantly more. As such, the additional limitations do not integrate the abstract idea into a practical application, or provide an inventive concept that transforms the claims into a patent eligible invention.
The apparatus claims are no different from the method claims in substance. “The equivalence of the method, system and media claims is readily apparent.” “The only difference between the claims is the form in which they were drafted.” (Bancorp). The method claims recite the abstract idea implemented on a generic computer, while the apparatus claims recite generic computer components configured to implement the same idea. Specifically, Claims 11 – 20 merely add the generic hardware noted above that nearly every computer will include. The apparatus claim’s requirement that the same method be performed with a programmed computer does not alter the method’s patentability under U.S.C. 101 (In re Grams). Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 - 8 and 11 – 18 are rejected under 35 U.S.C. 103 as being unpatentable over Berka et al.: (US PGPUB 2010/0292545 A1); in view of Krause et al.: (US PGPUB 2017/0323075 A1); in view of Ramarajan et al.: (US PGPUB 2012/0016690 A1); in view of Burd et al.: (US PGPUB 2021/0134433 A1).
CLAIMS 1 and 11
Berka discloses a physiological profiler system and method that includes the following limitations:
receive, from a user, a plurality of user physiological history data; wherein the user physiological history data was collected by a wearable device; identify, as a function of a disease state classifier, a plurality of disease states associated with the plurality of user physiological history data; and generating, by the computing device, a curative habitual pattern to alleviate the at least a disease state; (Berka Abstract, 0012, 0024, 0066, 0067, 0080, 0086, 0088 – 0090, 0097, 0173).
Berka discloses a system and method for evaluating the physiological state of an individual using historical physiological information (i.e. physiological history data) collected with a wearable device, and a statistical classifier (i.e. a disease state classifier) to identify the probability of the individual having or not having a plurality of disease states, by comparing a score to the same score of a large reference population. Berka discloses recommending treatment options (i.e. a curative habitual pattern) designed to address the identified deficiencies (i.e. alleviate the disease state).
With respect to the following limitations:
generate a ranked list of diseases, wherein generating further comprises: determining a plurality of disease impact score vectors associated with a plurality of diseases, generating a first objective function of the impact score vectors; and ranking the diseases according to optimization of the first objective function; (Krause Abstract, 0002, 0004, 0014, 0015, 0017, 0027, 0028, 0038).
The claims require generating a ranked list of diseases based on an overall impact of a disease in reduction of longevity and quality of life. The specification discloses that the ranked list may be generated by “receiving statistics reported from health reporting agencies”. Krause discloses a system and method for generating a ranked list of disease risk factors that are linked to any number of medical conditions (i.e. a plurality of diseases) based on a database containing information of a plurality of patients. Krause computes a series of impact scores for each risk factor, to generate a vector (or list) of risk factors (i.e. an impact score vector). The computing impact scores and ranking includes optimizing a predictive model (i.e. an objective function). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka so as to have included generating a list of diseases ranked by impact scores (i.e. disease impact score vectors), in accordance with the teaching of Krause, in order to provide an understanding of the risk of having certain diseases.
With respect to the following limitation:
matching, by the computing device, at least a disease state of the plurality of disease states to the ranked list of diseases; (Ramarajan 0008, 0009, 0012, 0028, 0043, 0077).
Berka discloses recommending a plurality of treatments for a particular disease state that may be combined, including evaluating the effect of the treatment using scores (0084, 0089, 0096, 0097); but does not disclose the recited matching steps. Ramarajan discloses a treatment related decision engine that includes receiving patient information and a medical condition, and obtaining a list of treatment options for the medical condition from a database of treatment options by matching the disease state to a database entry. Treatment options may include groups of treatments. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka/Krause so as to have included matching a patient medical condition to medical conditions in a treatment option database, scoring treatment options listed for the medical condition, and selecting a treatment based on the score, in accordance with the teaching of Ramarajan, in order to recommend the best treatment option to the patient for their particular medical condition.
wherein the curative habitual pattern contains a nutrition pattern containing a nutrition target for each eating occasion contained within the nutrition pattern; (Burd Abstract, 0006, 0053, 0057, 0060, 0061).
Berka is directed to determining “disorders or diseases affecting cognitive or emotional states”,(@ 0027); and further teaches that “models can be built for other diseases or states” (@ 0066, 0080). Berka discloses recommending or suggesting treatments (i.e. a curative habitual pattern), but does not expressly disclose a nutrition pattern. Burd discloses a system and method for treating a disorder with a dietary program or regimen, that is generated based on received patient medical and demographic information. The dietary regimen includes one or more individual meal recommendations for the patient during a time period; including determining the total amounts of protein, fat and carbohydrates, as well as target amounts. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka/Krause/Ramarajan so as to have included a nutrition pattern, in accordance with the teaching of Burd, in order to recommend the best treatment option to a patient for their diabetic medical condition.
CLAIMS 2 and 12
The combination of Berka/Krause/Ramarajan/Burd discloses the limitations above relative to Claims 1 and 11. Additionally, Berka discloses the following limitations:
wherein the user physiological history data is collected from a user questionnaire; (Berka 0029).
Berka discloses collecting responses to a subjective sleepiness questionnaire.
CLAIMS 7, 8, 17 and 18
The combination of Berka/Krause/Ramarajan/Burd discloses the limitations above relative to Claims 2 and 12. Additionally, Berka discloses the following limitations:
identify the plurality of disease states by determining a likelihood of each disease state of the plurality of disease states; weight each element of the ranked list, wherein weighting further comprises multiplying a likelihood of a disease state corresponding to an entry in the ranked list by an output of the first objective function for a corresponding disease of the plurality of diseases; (Berka 0067, 0069, 0080).
Berka discloses determining a likelihood of each disease state and weighting the entries on the ranked list.
CLAIMS 3, 4, 13 and 14
The combination of Berka/Krause/Ramarajan discloses the limitations above relative to Claims 2 and 12. Additionally, Ramarajan discloses the following limitations:
calculating a curative impact score of each curative habitual pattern candidate of a plurality of curative habitual pattern candidates; and selecting the curative habitual pattern from the plurality of curative habitual pattern candidates; (Ramarajan 0008 – 0011, 0023, 0077, 0084, 0094);
generating a second objective function of the plurality of curative habitual pattern candidates; and optimizing the second objective function; (Ramarajan 0008 – 0011, 0023, 0077, 0084, 0094, 0172);
receiving curative training data, the curative training data including a plurality of entries, each entry correlating a curative habitual pattern candidate with at least a curative impact element; training a curative machine-learning model as a function of the curative training data and a machine-learning process, wherein the curative machine-learning model inputs curative habitual pattern candidates and outputs curative impact vectors, each curative impact vector comprising at least a curative impact element; and generating the second objective function as an objective function of the curative impact vectors; (Ramarajan 0077, 0158 – 0161, 0171 – 0180)
Ramarajan discloses calculating a treatment impact score using various combinations of scores to maximize a score, and using machine learning with training data to obtain a treatment score. Ramarajan generates a ranked list of treatment options based on the treatment score and selects the treatment with the highest score. Examiner construes these techniques as objective functions. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka/Krause so as to have included calculating treatment impact scores using objective functions, in accordance with the teaching of Ramarajan, in order to allow various scores to be integrated into a final treatment score.
CLAIMS 5, 6, 15 and 16
The combination of Berka/Krause/Ramarajan discloses the limitations above relative to Claims 4 and 14. Additionally, Ramarajan discloses the following limitations:
wherein selecting the curative habitual pattern from the plurality of curative habitual pattern candidates further comprises comparing at least a curative impact vector to at least an impact score vector; selecting the curative habitual pattern as a function of the comparison of the curative impact vector to the at least an impact score vector; (Ramarajan 0009, 0012)
Ramarajan discloses calculating treatment scores (i.e. a curative impact vector) for a plurality of treatment options, based on historical outcomes that indicate the success of treatment and ranking the treatment options based on the treatment score. The treatment option having the highest score indicates the treatment that provides the greatest impact to the medical condition – (i.e. comparing the curative impact to the [disease] impact.) Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka/Krause/Ramarajan so as to have included comparing a treatment score to disease outcomes (i.e. the effect on the disease impact), in accordance with the teaching of Ramarajan, in order to provide an understanding of the outcome improvements for each treatment option.
Claims 9, 10, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Berka et al.: (US PGPUB 2010/0292545 A1) ; in view of Krause et al.: (US PGPUB 2017/0323075 A1); in view of Ramarajan et al.: (US PGPUB 2012/0016690 A1) and in view of Official Notice.
CLAIMS 9, 10, 19 and 20
The combination of Berka/Krause/Ramarajan discloses the limitations above relative to Claims 2 and 12. With respect to the following limitations:
wherein the first objective function further comprises a linear objective function;
wherein the first objective function further comprises a mixed integer objective function.
Linear functions are old and well-known, in particular, linear functions that have one variable constrained to be an integer, a fact for which Examiner take Official Notice. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the profiler system of Berka/Krause/Ramarajan so as to have included linear and mixed integer functions, in accordance with the Official Notice taken, merely as a matter of design choice.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PGPUB 2010/0070455 A1 to Halpern discloses a system and method for disease diagnosis that includes determining an age of onset.
“Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death”; Foreman et al.’ Global Health Metrics; 16 October, 2018 (referred to as Foreman herein); Foreman discloses the “Global Burden of Diseases, Injuries and Risk Factors Study”, that models the data provided by the 2016 GBD Study, including providing a ranked list of diseases generated by ranking according to Years of Lost Life (YLL) (i.e. an impact score vector).
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
Official replies to this Office action may now be submitted electronically by registered users of the EFS-Web system. Information on EFS-Web tools is available on the Internet at: http://www.uspto.gov/patents/process/file/efs/guidance/index.jsp. An EFS-Web Quick-Start Guide is available at: http://www.uspto.gov/ebc/portal/efs/quick-start.pdf.
Alternatively, official replies to this Office action may still be submitted by any one of fax, mail, or hand delivery. Faxed replies should be directed to the central fax at (571) 273-8300. Mailed replies should be addressed to “Commissioner for Patents, PO Box 1450, Alexandria, VA 22313-1450.” Hand delivered replies should be delivered to the “Customer Service Window, Randolph Building, 401 Dulany Street, Alexandria, VA 22314.”
/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 4 February, 2026