DETAILED ACTION
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 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.
Claims 2 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. Specifically, claim 2 recites by one or more processors. However, claim 1 previously introduced via one or more hardware processors in line 2. It is unclear if this is the same element, a different element, or related elements.
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.
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, 10, 21, 25-33 are rejected under 35 U.S.C. 103 as being unpatentable over Ludik et al. (hereinafter Ludik), U.S. Patent Application Publication 2012/0041910, in view of Bhatt et al. (hereinafter Bhatt), U.S. Patent Application Publication 2017/0286631, further in view of Tsay et al. (hereinafter Tsay) Action rules discovery: system DEAR2, method and experiments.
Regarding Claim 1, Ludik discloses a computer-implemented method, comprising:
accessing, via one or more hardware processors (HP), a knowledge model having a plurality of rules that (a) represent a clinical domain knowledge of an ontology and (b) form a data structure [“the operational data 14 is collected and stored in a database. The operational data, namely expert rules and expert actions” ¶26; “capturing of the expert rules is facilitated in software by using Decision Tables” ¶40; Fig. 5] at a medical records computer system (MRCS) associated with an electronic memory [“the engine referring to the computerized and programmed methodology” ¶46; “decision support system comprising a software implementation of a set of computer executable Instructions” ¶13; Examiner Note: computerized and programmed methodology and software implementation of a set of computer executable instructions require one or more processors and electronic memory];
identifying, by a web-based model-structure evaluator (WBMSE) associated with a set of tools operable to analyze and restructure the knowledge model and associated with the one or more hardware processors [“the engine referring to the computerized and programmed methodology used in fusing of the data driven and expert rules” ¶46], a model structure that describes the knowledge model [“the operational data 14 is collected and stored in a database. The operational data, namely expert rules and expert actions” ¶26; “capturing of the expert rules is facilitated in software by using Decision Tables” ¶40; Fig. 5] and that is associated with the plurality of rules representing the ontology;
determining, by the at least one web-based model-structure evaluator [“the engine referring to the computerized and programmed methodology used in fusing of the data driven and expert rules” ¶46], a first set of values indicating a data structure metric that (a) describes the model structure prior to adding a new knowledge-model rule to the data structure and (b) is associated with the plurality of rules [Fig. 5; Examiner Note: the number of rules in the example first table is a metric that describes the model structure prior to adding a new knowledge-model rule to the data structure and is associated with the plurality of rules] and the clinical domain knowledge of the ontology;
storing, to the electronic memory at the medical records computer system, the first set of values [“the engine referring to the computerized and programmed methodology” ¶46; “decision support system comprising a software implementation of a set of computer executable Instructions” ¶13; Fig. 5];
determining, via the at least one web-based model-structure evaluator and the one or more hardware processors [“the engine referring to the computerized and programmed methodology used in fusing of the data driven and expert rules” ¶46], a total possible number of different forms that can be generated from the plurality of rules;
determining that a set of two or more rules in the plurality of rules correspond to a same form in a plurality of forms [Fig. 5; Examiner Note: Form is interpreted as a table, being related to similar information. The rules displayed are all on the same table.];
determining that two or more rules in the set of two or more rules have different thresholds [“subset of rules classified as partially overlapping” ¶55; “contrasting rules” ¶56-57; Fig. 3-5; “temperature, flow and power” ¶56];
refactoring the different thresholds of the set of two or more rules into a composite threshold that condenses the different thresholds [Fig. 6-9; Examiner Note: These figures disclose rules with different thresholds being consolidated into fewer rules by condensing the different thresholds.];
generating, via the at least one web-based model-structure evaluator and the one or more hardware processors [“the engine referring to the computerized and programmed methodology used in fusing of the data driven and expert rules” ¶46], the new knowledge-model rule having the composite threshold [Fig. 5-9; Examiner Note: These figures disclose the consolidation of two or more rules into a single new rule.];
modifying the data structure at the medical records computer system, while maintaining a total quantity of different forms, that can be generated, corresponding to the determined total possible number of different forms that can be generated from the plurality of rules; and
electronically writing, via the at least one web-based model-structure evaluator and the one or more hardware processors and to the electronic memory at the medical records computer system, electronic encoded data that [“the engine referring to the computerized and programmed methodology” ¶46; “decision support system comprising a software implementation of a set of computer executable Instructions” ¶13]:
(a) identifies the total possible number of different forms; and
(b) quantifies, via a second set of values indicating the data structure metric after the modifying, how the modifying changes the data structure at the medical records computer system, wherein the second set of values differs from the first set of values [Fig. 5; Examiner Note: the number of rules in the example second table is a metric that quantifies how the modifying of the data structure changes the data structure, and the second value differs from the first value].
wherein modifying the data structure at the MRCS restructures the knowledge model, and comprises: (a) removing the set of two or more rules from the data structure at the MRCS; (b) adding, via one or both of the WBMSE and the HP, the new knowledge-model rule to the data structure at the MRCS; and (c) reducing a number, an average size, an average size of "if" premises or antecedents, or an average size of "then" statements or consequents, of rules in the data structure at the MRCS, via the removing and the adding [“create a fused data set (such as a consolidated rule set)” §11; Fig. 1, 5; “fusing of the data-driven rules generated in step 300 and the expert rules captured at step 400 to create a consolidated rule set” ¶42; Fig. 5-9; Examiner Note: the fusion of rules results in the same form (i.e., table topic) while adding a new consolidated rule and reducing the data structure size (e.g., fewer rules/columns)].
However, Ludik fails to explicitly disclose accessing, via one or more hardware processors, a knowledge model having a plurality of rules that (a) represent a clinical domain knowledge of an ontology and (b) form a data structure at a medical records computer system associated with an electronic memory;
identifying, by at least one web-based model-structure evaluator associated with a set of tools operable to analyze and restructure the knowledge model and associated with the one or more hardware processors, a model structure that describes the knowledge model and that is associated with the plurality of rules representing the ontology;
determining, by the at least one web-based model-structure evaluator, a first set of one or more values indicating a data structure metric that (a) describes the model structure prior to adding a new knowledge-model rule to the data structure and (b) is associated with the plurality of rules and the clinical domain knowledge of the ontology;
storing, to the electronic memory at the medical records computer system, the first set of one or more values;
determining, via the at least one web-based model-structure evaluator and the one or more hardware processors, a total possible number of different forms that can be generated from the plurality of rules;
generating, via the at least one web-based model-structure evaluator and the one or more hardware processors, the new knowledge-model rule having the composite threshold;
modifying the data structure at the medical records computer system, while maintaining a total quantity of different forms, that can be generated, corresponding to the determined total possible number of different forms that can be generated from the plurality of rules; and
electronically writing, via the at least one web-based model-structure evaluator and the one or more hardware processors and to the electronic memory at the medical records computer system, electronic encoded data that:
(i) identifies the total possible number of different forms; and
(ii) quantifies, via a second set of values indicating the data structure metric after the modifying, how the modifying of the data structure at the medical records computer system changes the data structure at the medical records computer system, wherein the second set of values differs from the first set of values.
Bhatt discloses accessing, via one or more hardware processors, a knowledge model having a plurality of rules that (a) represent a clinical domain knowledge of an ontology and (b) form a data structure at a medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26] associated with an electronic memory;
identifying, by a web-based [“accessible from various client devices through a thin client interface such as a web browser” ¶61] model-structure evaluator associated with a set of tools operable to analyze and restructure the knowledge model and associated with the one or more hardware processors, a model structure that describes the knowledge model and that is associated with the plurality of rules representing the ontology [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26];
determining, by the at least one web-based [“accessible from various client devices through a thin client interface such as a web browser” ¶61] model-structure evaluator, a first set of one or more values indicating a data structure metric that (a) describes the model structure prior to adding a new knowledge-model rule to the data structure and (b) is associated with the plurality of rules and the clinical domain knowledge of the ontology [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26];
storing, to the electronic memory at the medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26], the first set of values;
determining, via the at least one web-based [“accessible from various client devices through a thin client interface such as a web browser” ¶61] model-structure evaluator and the one or more hardware processors, a total possible number of different forms that can be generated from the plurality of rules;
generating, via the at least one web-based [“accessible from various client devices through a thin client interface such as a web browser” ¶61] model-structure evaluator and the one or more hardware processors, the new knowledge-model rule having the composite threshold;
modifying the data structure at the medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26], while maintaining a total quantity of different forms, that can be generated, corresponding to the determined total possible number of different forms that can be generated from the plurality of rules; and
electronically writing, via the at least one web-based [“accessible from various client devices through a thin client interface such as a web browser” ¶61] model-structure evaluator and the one or more hardware processors and to the electronic memory at the medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26], electronic encoded data that:
(i) identifies the total possible number of different forms; and
(ii) quantifies, via a second set of values indicating the data structure metric after the modifying, how the modifying of the data structure at the medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26] changes the data structure at the medical records computer system [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26], wherein the second set of values differs from the first set of values.
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik and Bhatt before him before the effective filing date of the claimed invention, to modify the method of Ludik to incorporate the medical rules and web-based access from Bhatt.
Given the advantage of storing medical information for ease and speed of retrieval when required, one having ordinary skill in the art would have been motivated to make this obvious modification.
However, Ludik fails to explicitly disclose determining, via the at least one web-based model-structure evaluator and the one or more hardware processors, a total possible number of different forms that can be generated from the plurality of rules;
modifying the data structure at the medical records computer system, while maintaining a total quantity of different forms, that can be generated, corresponding to the determined total possible number of different forms that can be generated from the plurality of rules; and
electronically writing, via the at least one web-based model-structure evaluator and the one or more hardware processors and to the electronic memory at the medical records computer system, electronic encoded data that:
(i) identifies the total possible number of different forms; and
(ii) quantifies, via a second set of values indicating the data structure metric after the modifying, how the modifying of the data structure at the medical records computer system changes the data structure at the medical records computer system, wherein the second set of values differs from the first set of values.
Tsay discloses determining, via the at least one web-based model-structure evaluator and the one or more hardware processors, a total possible number of different forms that can be generated from the plurality of rules [“partition the set of rules discovered from an information system…into a minimal number of subsets, each of which contains rules defining the same decision value” pg. 124 ¶4; “the number of tables representing them is equal to k” pg. 125 ¶1];
modifying the data structure at the medical records computer system, while maintaining a total quantity of different forms, that can be generated, corresponding to the determined total possible number of different forms that can be generated from the plurality of rules [“partition the set of rules discovered from an information system…into a minimal number of subsets, each of which contains rules defining the same decision value” pg. 124 ¶4; “the number of tables representing them is equal to k” pg. 125 ¶1]; and
electronically writing, via the at least one web-based model-structure evaluator and the one or more hardware processors and to the electronic memory at the medical records computer system, electronic encoded data that:
(i) identifies the total possible number of different forms [“partition the set of rules discovered from an information system…into a minimal number of subsets, each of which contains rules defining the same decision value” pg. 124 ¶4; “the number of tables representing them is equal to k” pg. 125 ¶1]; and
(ii) quantifies, via a second set of values indicating the data structure metric after the modifying, how the modifying of the data structure at the medical records computer system changes the data structure at the medical records computer system, wherein the second set of values differs from the first set of values.
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, and Tsay before him before the effective filing date of the claimed invention, to modify the combination to incorporate table creation approach of Tsay.
Given the advantage of grouping rules into tables based on the decision value which provides related rules in the same table for faster access when those types of decision are to be made, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 2, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses wherein determining the total possible number of different forms that can be generated from the plurality of rules comprises identifying a particular number, wherein the particular number indicates a quantity of the determined total possible number of different forms that can be generated from the plurality of rules and further comprising: tracing and identifying, by one or more processors, a number of distinct paths within each individual form [Fig. 5; Note: Each rule is a numbered and distinct path within the individual table which is identified and traced].
However, Ludik fails to explicitly disclose wherein determining the total possible number of different forms that can be generated from the plurality of rules comprises identifying a particular number, wherein the particular number indicates a quantity of the determined total possible number of different forms that can be generated from the plurality of rules and further comprising: tracing and identifying, by one or more processors, a number of distinct paths within each individual form.
Tsay discloses wherein determining the total possible number of different forms that can be generated from the plurality of rules comprises identifying a particular number [“the number of tables representing them is equal to k” pg. 125 ¶1], wherein the particular number indicates a quantity of the determined total possible number of different forms that can be generated from the plurality of rules [“all rules with the decision value di are selected and presented in a table format similar to table 3 in figure 1” pg. 125 ¶2; “partition the set of rules discovered from an information system…into a minimal number of subsets, each of which contains rules defining the same decision value” pg. 124 ¶4] and further comprising: tracing and identifying, by one or more processors, a number of distinct paths within each individual form.
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, and Tsay before him before the effective filing date of the claimed invention, to modify the combination to incorporate a particular number of total possible forms that can be generated from the plurality of rules.
Given the advantage of grouping rules into tables based on the decision value which provides related rules in the same table for faster access when those types of decision are to be made, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 3, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses further comprising determining, by the one or more hardware processors, a total number of different paths available within each of a plurality of different forms [Fig. 5; Note: Each rule is a numbered and distinct path within each individual table]; and performing, by the HP, one or both of (a) identifying, for each one of the different paths determined within each one of the different forms, at least one rule corresponding to the path and (b) identifying, for each of the different forms, the set of two or more rules that correspond to a matching path within the form [“create a fused data set (such as a consolidated rule set)” §11; Fig. 1, 5; “fusing of the data-driven rules generated in step 300 and the expert rules captured at step 400 to create a consolidated rule set” ¶42; Fig. 5-9; Examiner Note: the fusion of rules results in the same form (i.e., table topic) while adding a new consolidated rule and reducing the data structure size (e.g., fewer rules/columns)].
Claim 10 is rejected on the same grounds as claim 1.
Claims 21 is rejected on the same grounds as claim 1.
Regarding Claim 25, Ludik, Bhatt, and Tsay disclose the system of claim 21. Ludik further discloses wherein the first set of values and the second set of values each indicate a degree of diversity between each of a plurality of paths that can be generated from the form that corresponds to the set of two or more rules [Fig. 5; Note: rule consolidated from 9 rules to 4 rules indicates a degree of diversity between the possible paths/rules that can be used since there is no longer overlapping rules].
Regarding Claim 26, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses wherein the data structure at the medical records computer system is modified by reducing the total quantity of the plurality of rules in the knowledge model [Fig. 5] for the clinical domain knowledge of the ontology.
However, Ludik fails to explicitly disclose at the medical records computer system;
for the clinical domain knowledge of the ontology.
Bhatt discloses at the medical records computer [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26];
for the clinical domain knowledge of the ontology [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, and Tsay before him before the effective filing date of the claimed invention, to modify the combination to incorporate the medical rules from Bhatt.
Given the advantage of storing medical information for ease and speed of retrieval when required, one having ordinary skill in the art would have been motivated to make this obvious modification.
Claim 27 is rejected on the same grounds as claim 2.
Regarding Claim 28, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses wherein the determined set of two or more rules comprises more than two rules [Fig. 5].
However, Ludik fails to explicitly disclose wherein the determined total possible number of different forms that can be generated from the plurality of rules is a number.
Tsay discloses wherein the determined total possible number of different forms that can be generated from the plurality of rules is a number [“partition the set of rules discovered from an information system…into a minimal number of subsets, each of which contains rules defining the same decision value” pg. 124 ¶4; “the number of tables representing them is equal to k” pg. 125 ¶1].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, and Tsay before him before the effective filing date of the claimed invention, to modify the combination to incorporate table creation approach of Tsay.
Given the advantage of grouping rules into tables based on the decision value which provides related rules in the same table for faster access when those types of decision are to be made, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 29, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses wherein the electronic encoded data further indicates the first set of values [“stored in a database. The operational data, namely expert rules and expert actions, will be used as a source of expert rules of the process, a source of expert actions associated with the expert rules” ¶26; Fig. 5; Examiner Note: the number of rules in the example first table is a metric that describes the model structure prior to adding a new knowledge-model rule to the data structure and is associated with the plurality of rules].
Regarding Claim 30, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1.
However, Ludik fails to explicitly disclose wherein the first set of values and the set of second values each indicate a determined total possible number and quantity of different forms that can be generated from the plurality of rules.
Tsay discloses wherein the first set of values and the second set of values each indicate a determined total possible number and quantity of different forms that can be generated from the plurality of rules [“the number of tables representing them is equal to k” pg. 125 ¶1].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, and Tsay before him before the effective filing date of the claimed invention, to modify the combination to incorporate table creation approach of Tsay.
Given the advantage of grouping rules into tables based on the decision value which provides related rules in the same table for faster access when those types of decision are to be made, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 31, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10. Ludik further discloses wherein the refactoring comprises merging the different thresholds of the set of two or more rules to generate the composite threshold and merging the set of two or more rules into a composite rule [Fig. 5-9].
Regarding Claim 32, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10. Ludik further discloses wherein the set of tools comprises a model structure differentiation tool, a model output diversity tool, and a model restructuring tool [“decision support system comprising a software implementation of a set of computer executable instructions operable to execute a method of establishing a process decision support system” §13; Examiner Note: Since the tools are part of a web-based application, they are interpreted as software.].
Regarding Claim 33, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10. Ludik further discloses wherein the set of tools comprises a model structure differentiation tool that performs the identifying of the model structure, a model output diversity tool that performs the determining of the total possible number of different forms, and a model restructuring tool that performs the modifying [“decision support system comprising a software implementation of a set of computer executable instructions operable to execute a method of establishing a process decision support system” §13; Examiner Note: Since the tools are part of a web-based application, they are interpreted as software.].].
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Ludik, Bhatt, and Tsay, further in view of Sapir, U.S. Patent Application Publication 2006/0212412.
Regarding Claim 9, Ludik, Bhatt, and Tsay disclose the computer-implemented method of claim 1. Ludik further discloses further comprising identifying a plurality of rules within the knowledge model [Fig. 5]. Ludik, Bhatt, and Tsay disclose repeating, for each of the plurality of rules within the knowledge mode: the accessing, the identifying, the determining of the first set of values, the storing of the first set of values, the determining of the total possible number of different forms, the determining that the set of two or more rules correspond to the same form, the determining that the two or more rules have different thresholds, the refactoring, the generating, and the modifying including the removing and the adding [See Claim 1 rejection above].
However, Ludik fails to explicitly disclose repeating.
Sapir discloses repeating for each data item [“This procedure repeats until all chains have been evaluated” ¶83].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, Tsay, and Sapir before him before the effective filing date of the claimed invention, to modify the combination to incorporate the iteration based on data items to be processed of Sapir.
Given the advantage of ensuring accuracy and completeness by processing iteratively the procedure for each data item being analyzed, one having ordinary skill in the art would have been motivated to make this obvious modification.
Claims 11, 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Ludik, Bhatt, and Tsay, further in view of U.S. Pub. No. US 20170212748 A1 to Agnew, et al. (hereinafter, “Agnew”).
Regarding Claim 11, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the knowledge model further comprises a plurality of axioms, and wherein the operations further comprise:
generating, via the one or more hardware processors, a clinical knowledge axiom based on the refactoring the different thresholds of the set of two or more rules; and
modifying the knowledge model by adding the clinical knowledge axiom to the plurality of the axioms.
Agnew discloses wherein the knowledge model further comprises a plurality of axioms [“The ontology, being logic-based, embodies axioms contained the textual description of the BPMN specification.” ¶49; Examiner Note: Ontologies are a part of knowledge models which consist of axioms];
and wherein the operations further comprise: generating, via the one or more hardware processors, a clinical knowledge axiom based on the refactoring the different thresholds of the set of two or more rules [“The logic rule generation component 208 in FIG. 2 may extract axiom information 212 from a frozen ontology and generate, based on the axiom information 212, a set of logic rules.” ¶54; “The computer system 102 may comprise one or more physical processors” ¶42; Examiner Note: Logic rules are embodiments of axioms. Logic rules are to be generated base off refactoring as disclosed by Ludik above];
modifying the knowledge model by adding the clinical knowledge axiom to the plurality of the axioms [“In an operation 614, logic rules may be augmented with runtime rules of the computer program.” ¶83; Examiner Note: Modifying and adding the generated logic rules/axioms].
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the combination as modified to use the generation of axioms as disclosed by Agnew. The combination would have been obvious because a person of ordinary skill in the art would be motivated to improve variability of a knowledge model by encapsulating knowledge in various other forms.
However, Ludik fails to explicitly disclose clinical knowledge.
Bhatt discloses clinical knowledge [“access a set of medical dictionaries and rules, located in, for example, the predefined rules and dictionaries database” ¶26].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, Tsay and Agnew before him before the effective filing date of the claimed invention, to modify the combination to incorporate the medical information from Bhatt.
Given the advantage of rule consolidation in the medical field to increase speed and efficiency, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 14, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the operations further comprise:
generating, via the one or more hardware processors, a concept based on the refactoring the different thresholds of the set of two or more rules; and
and modifying the knowledge model by adding the at least one concept to an ontology of the knowledge model.
Agnew discloses wherein the operations further comprise:
generating, via the one or more hardware processors, a concept based on the refactoring the different thresholds of the set of two or more rules [“The logic rule generation component 208 in FIG. 2 may extract axiom information 212 from a frozen ontology and generate, based on the axiom information 212, a set of logic rules.” ¶54; “The computer system 102 may comprise one or more physical processors” ¶42; Examiner Note: Logic rules are embodiments of axioms. Logic rules are to be generated base off refactoring as disclosed by Ludik above. The concept being a logical rule which consists of axioms];
and modifying the knowledge model by adding the at least one concept to an ontology of the knowledge model [“In an operation 614, logic rules may be augmented with runtime rules of the computer program.” ¶83; Fig. 2; Examiner Note: Modifying and adding the generated concepts/logic rules/axioms to the ontology of a knowledge model].
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the combination as modified with the teachings of Agnew for at least the same reasons as discussed above in claim 11.
Regarding Claim 15, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the operations further comprise determining that a portion of the forms that are can be generated is reusable for one or more other ontologies
Agnew discloses wherein the operations further comprise determining that a portion of the forms that are can be generated is reusable for one or more other ontologies [“For example, another domain-specific ontology in the different domain of interest and another general ontology instance corresponding to the other application may be obtained, and another supplemental information related to the different functionalities may be generated based on the other general ontology instance and domain-specific ontology and provided as input to the computer program.” ¶99; Examiner Note: Reusing forms for other domain ontologies].
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the combination as modified with the teachings of Agnew for at least the same reasons as discussed above in claim 11
Claim 13 are rejected under 35 U.S.C. 103 as being unpatentable over Ludik, Bhatt, Tsay, further in view of Agnew, and further in view of U.S. Pub. No. US 20130204830 A1 to Franke (hereinafter, “Franke”).
Regarding Claim 13, Ludik, Bhatt, Tsay, and Agnew disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the knowledge model further comprises a plurality of axioms.
Agnew discloses wherein the knowledge model further comprises a plurality of axioms [“The ontology, being logic-based, embodies axioms contained the textual description of the BPMN specification.” ¶49; Examiner Note: Ontologies are a part of knowledge models which consist of axioms].
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the combination as modified to use the generation of axioms as disclosed by Agnew. The combination would have been obvious because a person of ordinary skill in the art would be motivated to improve variability of a knowledge model by encapsulating knowledge in various other forms.
Ludik fails to disclose wherein the knowledge model further comprises a plurality of axioms, and wherein the operations further comprise restructuring the knowledge model by removing the one or more of the plurality of rules determined to be redundant based on at least one of the plurality of axioms, from the knowledge model.
Franke further discloses wherein the operations further comprise restructuring the knowledge model by removing the one or more of the plurality of rules determined to be redundant based on at least one of the plurality of axioms, from the knowledge model [ “Complexity may also be reduced by discarding redundant rules, such as rules providing only trivial associations.” ¶15].
It would have been obvious to one having ordinary skill in the art, having the teachings of Ludik, Bhatt, Tsay, Agnew, and Franke before him before the effective filing date of the claimed invention, to modify the combination to incorporate the medical information from Bhatt.
Given the advantage of increased efficiency and speed by removing duplicate data, one having ordinary skill in the art would have been motivated to make this obvious modification.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Ludik, Bhatt, and Tsay, further in view of WIPO No. WO 2017188987 A2 to Perez, et al. (hereinafter, “Perez”).
Regarding Claim 17, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the operations further comprise:
determining that two or more paths of a plurality of paths are input equivalent paths when the two or more paths have a distribution overlap of at least 90%;
and designating that the two or more paths are matching paths.
Perez discloses wherein the operations further comprise:
determining that two or more paths of a plurality of paths are input equivalent paths when the two or more paths have a distribution overlap of at least 90% [“Instructions 122 may determine, for each pair of rules in the set of rules, a respective pair overlap between calculated hypervolumes for each individual rule, In some examples, instructions 122 may determine the respective pair overlap by determining a respective Jaccard similarity for the respective sets of hypershapes associated with each pair of rules.” ¶24];
and designating that the two or more paths are matching paths [“A first rule and second rule may be combined as a new individual rule in the set of rules based on overlaps between the calculated hypervolurnes.” ¶13; Examiner Note: Determining that the rules are input equivalent path based on the similarity thus determining to combine them].
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the combination as modified to determine that rules are input equivalent paths as disclosed by Perez. The combination would have been obvious because a person of ordinary skill in the art would be motivated to identify if paths are input equivalent quicker so that input equivalent paths may be combined to reduce redundancy of the knowledge base.
Claims 20 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Ludik, Bhatt, and Tsay, and further in view of U.S. Pub. No. US 20170124269 A1 to McNair, et al. (hereinafter, “McNair”)
Regarding Claim 20, Ludik, Bhatt, and Tsay disclose the one or more non-transitory media of claim 10.
However, Ludik fails to explicitly disclose wherein the operations further comprise, subsequent to modifying the data structure at the medical records computer system:
obtaining electronic records from a plurality of diverse systems, the plurality of diverse record systems having the electronic records in different data formats;
reconciling the electronic records obtained from the plurality of diverse systems with one another using the knowledge model; and
and generating inferential clinical knowledge based on reconciling the electronic records.
McNair discloses wherein the operations further comprise, subsequent to modifying the data structure at the medical records computer system:
obtaining electronic records from a plurality of diverse systems, the plurality of diverse record systems having the electronic records in different data formats [“At a step 40230, a target set of clinical information associated with a target patient is received from a second set of electronic health records” ¶145; “Embodiments of electronic health record (EHR) systems 160, 162, or 164 include one or more data stores of health records… Example embodiments of EHRs 160, 162, or 164 include hospital, ambulatory, clinic, health exchange, and health plan records systems. EHR systems 160, 162, and 164 may further include record systems, which store real-time or near real-time patient (or user) information,.. Further, in some embodiments EHRs 160, 162, and 164 are affiliated with two or more separate health care entities that use two or more distinct nomenclatures.” ¶30; Examiner Note: Obtaining electronic records that are from diverse systems that have data in different formats];
reconciling the electronic records obtained from the plurality of diverse systems with one another using the knowledge model [“In some embodiments, system 3200 also includes a reconcile component 3260 for learning and relating results from multiple sources” ¶104];
and generating inferential clinical knowledge based on reconciling the electronic records [“A concept recognition component 306 performs synonymic discovery and is generally responsible for reconciling terms used by the various medical organizations, and in some embodiments is facilitated by one or more agents 2135 of FIG. 1C. For instance, if a first medical organization calls a white blood cell count test WBC and a second medical organization calls the same test WC, the concept recognition component 306 would have this information stored to determine that both terms are referring to the same test.” ¶110].
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to the combination as modified to reconcile electronic records as disclosed by McNair. The combination would have been obvious because a person of ordinary skill in the art would be motivated to gain new knowledge regarding electronic records such that the knowledge of a knowledge model can be further increased thus improving model variability.
Claim 24 is rejected on the same grounds as claim 20.
Examiner’s Note
The Examiner respectfully requests of the Applicant in preparing responses, to fully consider the entirety of the reference(s) as potentially teaching all or part of the claimed invention. It is noted, REFERENCES ARE RELEVANT AS PRIOR ART FOR ALL THEY CONTAIN. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). A reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art, including non-preferred embodiments (see MPEP 2123). The Examiner has cited particular locations in the reference(s) as applied to the claim(s) above for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim(s), typically other passages and figures will apply as well.
Additionally, any claim amendments for any reason should include remarks indicating clear support in the originally filed specification.
Response to Arguments
Regarding the 101 rejections, Applicant’s arguments regarding the current claim language were found persuasive. Accordingly, the rejections are withdrawn due to amendments and arguments.
Regarding the prior art rejections, Applicant's arguments have been fully considered but have been found unpersuasive. Applicant argues that 1) Ludik is not analogous art because it deals with industrial processing and not a clinical domain, and 2) Ludik fails to disclose a total possible number of forms. Examiner disagrees for at least the following reasons.
First, in response to applicant's argument that Ludik is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Ludik deals with the same problem as the instant claims. Specifically, implementing rule consolidation. Furthermore, Bhatt was used in the rejection of the clinical/medical information system aspects of the claims. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Second, while Ludik discloses the rule consolidation using the tables as forms, it does not specifically indicate the number of tables (i.e., forms). However, this element is disclosed by Tsay. Again, in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
It is the combination of references which disclose the claims. For at least these reasons, the rejections are maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The following references were found during the examination of this patent application and were found to be relevant to patentability. Applicant is advised to review these references prior to responding to this Office action.
Klemettinen et al. (Finding Interesting Rules from Large Sets of Discovered Association Rules) discloses a simple formalism of rule templates to make it possible to easily describe the structure of interesting rules.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT H BEJCEK II whose telephone number is (571)270-3610. The examiner can normally be reached Monday - Friday: 9:00am - 5:00pm.
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, Michelle T. Bechtold can be reached at (571) 431-0762. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/R.B./ Examiner, Art Unit 2148
/MICHELLE T BECHTOLD/ Supervisory Patent Examiner, Art Unit 2148
