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 .
Notice to Applicant
This communication is in response to the amendment filed 03/31/2026. Claims 1-20 are presented for examination.
Drawings
The drawings were received on 03/31/2026. These drawings are acceptable.
Subject Matter Free of Prior Art
Claim(s) 1-20 are allowable over prior art because the prior art of record fail to expressly teach or suggest, either alone or in combination, the features found within the independent claims, in particular: “generate a semantic graph representation based on at least the set of segmented texts that is representative of a semantic relationship as a medical semantic type between at least a plurality of nodes; extract one or more medical entities based on an annotated medical domain ontology from the generated semantic graph representation; prune a set of irrelevant information based on the annotated medical domain ontology applied to the generated semantic graph representation; and generate a medically relevant summary for the medical report based on the extracted one or more medical entities and excluding the pruned set of irrelevant information based on the annotated medical domain ontology.” Because the prior art does not teach or disclose the above features in the specific manner and combinations recited in independent claims 1, 12, 19, claims 1, 12, 19 are hereby deemed to be allowable over prior art. Originally numbered dependent claims 2-11, 13-18, 20 incorporate the allowable features of originally numbered independent claims 1, 12, 19, through dependency, respectively.
However, the claims are still rejected under 101.
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) without significantly more. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Claim 1 is drawn to a system which is within the four statutory categories (i.e., machine). Claim 12 is drawn to a system which is within the four statutory categories (i.e., machine). Claim 19 is drawn to a method which is within the four statutory categories (i.e., method).
Independent claim 12 (which is representative of independent claims 1, 19) recites receive one or more medical records associated with the patient for summarization for the medical report of the patient; extract one or more potential headings from one or more phrases of a medical record text of the one or more medical records; compare the one or more potential headings with one or more keyword headings of a heading seed set to generate, upon a match, one or more segmentation headings; segment…one or more sections of the medical record text of the one or more medical records as a set of segmented texts based on the one or more segmentation headings; classify…the set of segmented texts with one or more pre-defined medical tags to generate one or more groups of classified text, wherein the one or more groups of classified text comprise a number of predefined categories; generate a semantic graph representation based on at least the one or more groups of classified text that is representative of a semantic relationship as a medical semantic type between at least a plurality of nodes; extract one or more medical entities based on an annotated medical domain ontology from the generated semantic graph representation, wherein the annotated medical domain ontology comprises a medical ontology dataset configured to tag as an annotation the one or more medical entities along with a corresponding medical semantic type; prune a set of irrelevant information based on the annotated medical domain ontology applied to the generated semantic graph representation; and generate a medically relevant summary for the medical report based on the extracted one or more medical entities and excluding the pruned set of irrelevant information based on the annotated medical domain ontology.
Under its broadest reasonable interpretation, the limitations noted above, as drafted, covers certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people…following rules or instructions), but for the recitation of generic computer components. That is, other than reciting a “system” (claims 1, 12), the claim encompasses rules or instructions to collect data, analyze the collected data, and output relevant data based on the analysis accordingly. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Claim 1 recites additional elements (i.e., A system comprising: a processor; and a memory storing computer-executable instructions; a text segmentation algorithm of an artificial intelligence model). Claim 12 recites additional elements (i.e., A system comprising: a processor; and a memory storing computer-executable instructions; a text segmentation algorithm of an artificial intelligence model; a text classification algorithm of the artificial intelligence model). Claim 19 recites additional elements (i.e., a text segmentation algorithm of an artificial intelligence model). Looking to the specifications, a computing system having a processor, memory storing computer-executable instructions is described at a high level of generality (¶ 0022-0025), such that it amounts to no more than mere instructions to apply the exception using generic computer components. Also, “an artificial intelligence model” with “a text segmentation algorithm” and “a text classification algorithm” is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The 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. Accordingly, the claims are directed to an abstract idea.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. The use of a general purpose computer or computers (i.e., a computing system having a processor, memory storing computer-executable instructions) amounts to no more than mere instructions to apply the exception using generic computer components and does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Also, “an artificial intelligence model” with “a text segmentation algorithm” and “a text classification algorithm” is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook; similarly, the current invention merely limits the claimed calculations to the healthcare industry which does not impose meaningful limits on the scope of the claim. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
Dependent claims 2-11, 13-18, 20 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 3-11, 13-18 further define the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claims 2, 20 further recites the additional elements of “a text classification algorithm of the artificial intelligence model,” which is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims as a whole do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Certain Methods of Organizing Human Activity,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Response to Arguments
Applicant's arguments filed 03/31/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 03/31/2026.
In the remarks, Applicant argues in substance that:
Regarding the 101 rejections,
“the recitations of independent claim 1 (and similarly independent claims 12 and 19) including are directed to a field of artificial intelligence and machine learning (AI/ML) including Al semantic graph generation for an intelligent pipeline summarization for a medical report and are not in a group of (a) mathematical concepts, (b) certain methods of organizing human activities, or (c) mental processes as such recited features directed to AI/ML and Al semantic graph generation are not practically performed in a human mind… none of the present independent claims 1, 12, and 1 even explicitly recite social activities, teaching, and following rules or instructions with respect to managing personal behavior, and relationships or interactions between people as features, and thus would not be considered to "recite" an alleged judicial exception of certain methods of organizing human activity”;
“the claims directed to AI/ML and semantic graph generation for intelligent pipeline summarization for a medical report to apply recited features in a manner not practically performed in a human mind are patent eligible under a streamlined analysis, similar to a Streamlined Eligibility Example in the Interim Guidelines finding patent eligible a claim directed to a robotic arm assembly having a control system that operates using certain mathematical relationships (e.g., use of a mathematical concept in a manner not practically performed in a human mind and in a manner that does not tie up use of the mathematical concept to be patent eligible under Step 2A in a streamlined analysis)… Similar to EXAMPLE 40 of the 2019 PEG that found a judicial exception integrated into a practical application through recitation of a meaningful limitation of at least the practical application of collecting additional Netflow protocol data relating to traffic based on a meaningful limitation of when the collected network delay, packet loss, or jitter is greater than the predefined threshold, the independent claims integrate any alleged judicial exception into a practical application of at least (1) a practical application of "generate a medically relevant summary for the medical report that is based on a meaningful limitation of "based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]"… similar to the patent eligible claim 1 of EXAMPLE 42… the present claims recite a specific improvement involving conversion of input data associated with a medical report (e.g., that can be unstructured data, for example), into a generated semantic graph representation, to further generate a medically relevant summary for the medical report as a standardized output (such as further recited in claim 3 to follow a standardized format) in real time that is shareable with others, as well as a practical application of an efficient and optimized AI based automation of generation of the medically relevant summary based on meaningfully limited semantic graph representation application and pruning. As claim 1 of EXAMPLE 42 improves efficiencies by converting information into a standardized format, automatically generating a message based on the standardized format, and transmitting that message to all users regarding of information input format by a user, the present claims further improve efficiencies by intelligent pipeline summarization for a medical report to generate a medically relevant summary that is meaningfully limited to prune and exclude irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation] to avoid system noise and inefficiencies associated with processing unwanted data… Just as claim 3 of EXAMPLE 47 is found patent eligible… independent claim 1 (and similarly independent claims 12 and 19) is patent eligible as a human mind is not equipped to perform the analogous recited features of similar remedial actions as a practical integrated of any alleged judicial exception, also providing specific intelligent AI solutions… the technical improvement of generation of a medically relevant summary determined by an intelligent AI generated semantic graph representation to "generate a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]" [is] similar to claim 2 of EXAMPLE 48 excluding a pruned set of irrelevant information to thus similarly exclude the unwanted data and concurrently reduce system noise and inefficiencies as a patent eligible improvement to technology and/or a technical field”; and
“they at least affect an improvement in the technology and/or technical field (see Alice) of intelligent pipeline summarization for a medical report, which improvement is based on generation of "a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation], which allows for the benefits of more streamlined and efficient method for generating a medically relevant summary using meaningfully limited and relevant data while pruning and excluded unwanted data per specific algorithms applied to a generated semantic graph representation to improve processing efficiencies and accuracy and reduce system noise. Indeed, as set forth herein, the present claim recitations additionally reflect an improvement in the recited technology to reduce system noise from information that is undesired, which further avoids using additional computing processing resources and provides more efficient processing technology to be patent eligible similar to Enfish… independent claims 1, 12, and 1 further recite an ordered combination of features that is not well-understood, routine, or conventional and are thus patent eligible… The lack of novelty and obviousness rejections demonstrate that the claims of the present application are not well-understood, routine, or conventional, and the Examiner provides no evidence (and thus insufficient support) that the recited elements (individually or combination) were widely prevalent or in common use in the relevant industry.”
It is respectfully submitted that Examiner has considered Applicant’s arguments and does not find them persuasive. Examiner has attempted to address all of the arguments presented by Applicant; however, any arguments inadvertently not addressed are not persuasive for at least the following reasons:
In response to Applicant’s argument that (a) regarding the 101 rejections,
“the recitations of independent claim 1 (and similarly independent claims 12 and 19) including are directed to a field of artificial intelligence and machine learning (AI/ML) including Al semantic graph generation for an intelligent pipeline summarization for a medical report and are not in a group of (a) mathematical concepts, (b) certain methods of organizing human activities, or (c) mental processes as such recited features directed to AI/ML and Al semantic graph generation are not practically performed in a human mind… none of the present independent claims 1, 12, and 1 even explicitly recite social activities, teaching, and following rules or instructions with respect to managing personal behavior, and relationships or interactions between people as features, and thus would not be considered to "recite" an alleged judicial exception of certain methods of organizing human activity”:
It is respectfully submitted that per broadest reasonable interpretation of the claim in light of the specification, the claims of the present invention encompass the activity of (to paraphrase) rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, which covers the sub-grouping of managing personal behavior or relationships or interactions between people in the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, and not the “Mathematical Concepts” grouping or a concept performed in the human mind in the “Mental Processes” grouping, as Applicant now argues. Put another way, the claimed invention amounts to a series of rules or steps that users (i.e., doctor) would follow to collect and analyze relevant data to generate a medical summary for a patient. This is an abstract idea. That the steps are performed on a well-known, general purpose computer (i.e., a computing system having a processor, memory storing computer-executable instructions) does not remove the invention from being directed to an abstract idea.
Applicant argues “recited features directed to AI/ML and Al semantic graph generation.” However, the claims to which Applicant seem to refer (i.e., “an artificial intelligence model” with “a text segmentation algorithm” and “a text classification algorithm”) not interpreted as part of the abstract idea, but an additional element which is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Furthermore, it is noted that the features upon which applicant relies (i.e., “machine learning”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant argues “none of the present independent claims 1, 12, and 1 even explicitly recite social activities, teaching, and following rules or instructions with respect to managing personal behavior, and relationships or interactions between people as features, and thus would not be considered to "recite" an alleged judicial exception of certain methods of organizing human activity.” However, per MPEP § 2106.04(a), “Examiners should determine whether a claim recites an abstract idea by (1) identifying the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea, and (2) determining whether the identified limitations(s) fall within at least one of the groupings of abstract ideas listed above,” which Examiner has done as stated previously in Office Action dated 12/31/2025 and above.
Thus, the claims are directed to an abstract idea
“the claims directed to AI/ML and semantic graph generation for intelligent pipeline summarization for a medical report to apply recited features in a manner not practically performed in a human mind are patent eligible under a streamlined analysis, similar to a Streamlined Eligibility Example in the Interim Guidelines finding patent eligible a claim directed to a robotic arm assembly having a control system that operates using certain mathematical relationships (e.g., use of a mathematical concept in a manner not practically performed in a human mind and in a manner that does not tie up use of the mathematical concept to be patent eligible under Step 2A in a streamlined analysis)… Similar to EXAMPLE 40 of the 2019 PEG that found a judicial exception integrated into a practical application through recitation of a meaningful limitation of at least the practical application of collecting additional Netflow protocol data relating to traffic based on a meaningful limitation of when the collected network delay, packet loss, or jitter is greater than the predefined threshold, the independent claims integrate any alleged judicial exception into a practical application of at least (1) a practical application of "generate a medically relevant summary for the medical report that is based on a meaningful limitation of "based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]"… similar to the patent eligible claim 1 of EXAMPLE 42… the present claims recite a specific improvement involving conversion of input data associated with a medical report (e.g., that can be unstructured data, for example), into a generated semantic graph representation, to further generate a medically relevant summary for the medical report as a standardized output (such as further recited in claim 3 to follow a standardized format) in real time that is shareable with others, as well as a practical application of an efficient and optimized AI based automation of generation of the medically relevant summary based on meaningfully limited semantic graph representation application and pruning. As claim 1 of EXAMPLE 42 improves efficiencies by converting information into a standardized format, automatically generating a message based on the standardized format, and transmitting that message to all users regarding of information input format by a user, the present claims further improve efficiencies by intelligent pipeline summarization for a medical report to generate a medically relevant summary that is meaningfully limited to prune and exclude irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation] to avoid system noise and inefficiencies associated with processing unwanted data… Just as claim 3 of EXAMPLE 47 is found patent eligible… independent claim 1 (and similarly independent claims 12 and 19) is patent eligible as a human mind is not equipped to perform the analogous recited features of similar remedial actions as a practical integrated of any alleged judicial exception, also providing specific intelligent AI solutions… the technical improvement of generation of a medically relevant summary determined by an intelligent AI generated semantic graph representation to "generate a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]" [is] similar to claim 2 of EXAMPLE 48 excluding a pruned set of irrelevant information to thus similarly exclude the unwanted data and concurrently reduce system noise and inefficiencies as a patent eligible improvement to technology and/or a technical field”:
Applicant argues “the claims directed to AI/ML and semantic graph generation for intelligent pipeline summarization for a medical report to apply recited features in a manner not practically performed in a human mind are patent eligible under a streamlined analysis, similar to a Streamlined Eligibility Example in the Interim Guidelines finding patent eligible a claim directed to a robotic arm assembly having a control system that operates using certain mathematical relationships (e.g., use of a mathematical concept in a manner not practically performed in a human mind and in a manner that does not tie up use of the mathematical concept to be patent eligible under Step 2A in a streamlined analysis).” However, Applicant fails to specify how “the claims directed to AI/ML and semantic graph generation for intelligent pipeline summarization for a medical report to apply recited features in a manner not practically performed in a human mind are patent eligible under a streamlined analysis, similar to a Streamlined Eligibility Example in the Interim Guidelines finding patent eligible a claim directed to a robotic arm assembly having a control system that operates using certain mathematical relationships (e.g., use of a mathematical concept in a manner not practically performed in a human mind and in a manner that does not tie up use of the mathematical concept to be patent eligible under Step 2A in a streamlined analysis).” Regardless, the claims of the present invention covers the sub-grouping of managing personal behavior or relationships or interactions between people in the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, and not the “Mathematical Concepts” grouping or a concept performed in the human mind in the “Mental Processes” grouping, as Applicant now seems to argue.
Applicant argues “Similar to EXAMPLE 40 of the 2019 PEG that found a judicial exception integrated into a practical application through recitation of a meaningful limitation of at least the practical application of collecting additional Netflow protocol data relating to traffic based on a meaningful limitation of when the collected network delay, packet loss, or jitter is greater than the predefined threshold, the independent claims integrate any alleged judicial exception into a practical application of at least (1) a practical application of "generate a medically relevant summary for the medical report that is based on a meaningful limitation of "based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]."” However, Applicant fails to specify how the claims of the present invention are “Similar to EXAMPLE 40” and how "generate a medically relevant summary for the medical report that is based on a meaningful limitation of "based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]” is a practical application. Regardless, the claims of the present invention are different from the claim limitations of those found eligible in Example 40. Even if the claim limitations of the present invention are similar to that of the claims found eligible (and they are not similar), the claimed inventions are fundamentally different in scope and should be interpreted based on the asserted fact patterns; other fact patterns may have different eligibility outcomes, as is the case with the claims of the present invention. Unlike the claims found eligible in Example 40, the claims of the present invention do not provide an improvement in the functioning of a computer, or an improvement to other technology or technical field. Furthermore, the claim limitations to which Applicant refer (i.e., "generate a medically relevant summary for the medical report that is based on a meaningful limitation of "based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]") are interpreted as part of the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, and not additional elements to be interpreted in Step 2A, Prong Two.
Applicant argues “similar to the patent eligible claim 1 of EXAMPLE 42… the present claims recite a specific improvement involving conversion of input data associated with a medical report (e.g., that can be unstructured data, for example), into a generated semantic graph representation, to further generate a medically relevant summary for the medical report as a standardized output (such as further recited in claim 3 to follow a standardized format) in real time that is shareable with others, as well as a practical application of an efficient and optimized AI based automation of generation of the medically relevant summary based on meaningfully limited semantic graph representation application and pruning. As claim 1 of EXAMPLE 42 improves efficiencies by converting information into a standardized format, automatically generating a message based on the standardized format, and transmitting that message to all users regarding of information input format by a user, the present claims further improve efficiencies by intelligent pipeline summarization for a medical report to generate a medically relevant summary that is meaningfully limited to prune and exclude irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation] to avoid system noise and inefficiencies associated with processing unwanted data.” However, the claim limitations to which Applicant seem to refer as "conversion of input data associated with a medical report (e.g., that can be unstructured data, for example), into a generated semantic graph representation, to further generate a medically relevant summary for the medical report as a standardized output,” “generation of the medically relevant summary based on meaningfully limited semantic graph representation application and pruning,” “generate a medically relevant summary that is meaningfully limited to prune and exclude irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]” are interpreted as part of the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, and not additional elements to be interpreted in Step 2A, Prong Two. The “an artificial intelligence model” with “a text segmentation algorithm” and “a text classification algorithm” is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Furthermore, it is noted that the features upon which applicant relies (i.e., “real time”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Furthermore, the claims of the present invention are different from the claim limitations of those found eligible in Example 42. Even if the claim limitations of the present invention are similar to that of the claims found eligible (and they are not similar), the claimed inventions are fundamentally different in scope and should be interpreted based on the asserted fact patterns; other fact patterns may have different eligibility outcomes, as is the case with the claims of the present invention. Unlike the claims found eligible in Example 42, the claims of the present invention do not provide an improvement in the functioning of a computer, or an improvement to other technology or technical field. Even if the claims provide the alleged improvements (i.e., “avoid system noise and inefficiencies associated with processing unwanted data”), any alleged benefits of the invention are at best, an improvement to the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly. However, an improved abstract idea is still an abstract idea and the claims do not provide a technical improvement.
Applicant argues “Just as claim 3 of EXAMPLE 47 is found patent eligible… independent claim 1 (and similarly independent claims 12 and 19) is patent eligible as a human mind is not equipped to perform the analogous recited features of similar remedial actions as a practical integrated of any alleged judicial exception, also providing specific intelligent AI solutions.” However, the claims of the present invention are different from the claim limitations of those found eligible in Example 47. Even if the claim limitations of the present invention are similar to that of the claims found eligible (and they are not similar), the claimed inventions are fundamentally different in scope and should be interpreted based on the asserted fact patterns; other fact patterns may have different eligibility outcomes, as is the case with the claims of the present invention. Unlike the claims found eligible in Example 47, the claims of the present invention covers the sub-grouping of managing personal behavior or relationships or interactions between people in the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, and not a concept performed in the human mind in the “Mental Processes” grouping, as Applicant now seems to argue. Furthermore, the claims of the present invention do not provide an improvement in the functioning of a computer, or an improvement to other technology or technical field.
Applicant argues “the technical improvement of generation of a medically relevant summary determined by an intelligent AI generated semantic graph representation to "generate a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation]" [is] similar to claim 2 of EXAMPLE 48 excluding a pruned set of irrelevant information to thus similarly exclude the unwanted data and concurrently reduce system noise and inefficiencies as a patent eligible improvement to technology and/or a technical field.” However, claim 2 of Example 48 was not found eligible for “excluding” information; claim 2 of Example 48 was found eligible for providing an improvement in the functioning of a computer, or an improvement to other technology or technical field, which the claims of the present invention do not, as noted previously above. Furthermore, the claims of the present invention are different from the claim limitations of those found eligible in claim 2 of Example 48. Even if the claim limitations of the present invention are similar to that of the claims found eligible (and they are not similar), the claimed inventions are fundamentally different in scope and should be interpreted based on the asserted fact patterns; other fact patterns may have different eligibility outcomes, as is the case with the claims of the present invention. Unlike the claims found eligible in Example 47, the claims of the present invention covers the sub-grouping of managing personal behavior or relationships or interactions between people in the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, and not the “Mathematical Concepts” grouping or a concept performed in the human mind in the “Mental Processes” grouping, as Applicant now seems to argue.
Thus, the claim as a whole does not integrate the recited judicial exception into a practical application.
“they at least affect an improvement in the technology and/or technical field (see Alice) of intelligent pipeline summarization for a medical report, which improvement is based on generation of "a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation], which allows for the benefits of more streamlined and efficient method for generating a medically relevant summary using meaningfully limited and relevant data while pruning and excluded unwanted data per specific algorithms applied to a generated semantic graph representation to improve processing efficiencies and accuracy and reduce system noise. Indeed, as set forth herein, the present claim recitations additionally reflect an improvement in the recited technology to reduce system noise from information that is undesired, which further avoids using additional computing processing resources and provides more efficient processing technology to be patent eligible similar to Enfish… independent claims 1, 12, and 1 further recite an ordered combination of features that is not well-understood, routine, or conventional and are thus patent eligible… The lack of novelty and obviousness rejections demonstrate that the claims of the present application are not well-understood, routine, or conventional, and the Examiner provides no evidence (and thus insufficient support) that the recited elements (individually or combination) were widely prevalent or in common use in the relevant industry”:
Applicant argues “an improvement in the technology and/or technical field (see Alice) of intelligent pipeline summarization for a medical report, which improvement is based on generation of "a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation], which allows for the benefits of more streamlined and efficient method for generating a medically relevant summary using meaningfully limited and relevant data while pruning and excluded unwanted data per specific algorithms applied to a generated semantic graph representation.” However, the claim limitations to which Applicant seem to refer as "generation of "a medically relevant summary for the medical report based on the extracted one or more medical entities [from a generated semantic graph representation] and excluding the pruned set of irrelevant information based on the annotated medical domain ontology [applied to the generated semantic graph representation],” “generating a medically relevant summary using meaningfully limited and relevant data while pruning and excluded unwanted data per specific algorithms applied to a generated semantic graph representation” are interpreted as part of the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, and not additional elements to be interpreted in Step 2B.
Applicant argues “improve processing efficiencies and accuracy and reduce system noise. Indeed, as set forth herein, the present claim recitations additionally reflect an improvement in the recited technology to reduce system noise from information that is undesired, which further avoids using additional computing processing resources and provides more efficient processing technology to be patent eligible similar to Enfish.” However, the claim limitations to which Applicant seem to refer providing the alleged improvements are interpreted as part of the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, and not additional elements to be interpreted in Step 2B. Furthermore, the claims of the present invention are different from the claim limitations of those found eligible in Enfish. Even if the claim limitations of the present invention are similar to that of the claims found eligible (and they are not similar), the claimed inventions are fundamentally different in scope and should be interpreted based on the asserted fact patterns; other fact patterns may have different eligibility outcomes, as is the case with the claims of the present invention. Unlike the claims found eligible in Enfish, the claims of the present invention do not provide an improvement in the functioning of a computer, or an improvement to other technology or technical field. Even if the claims provide the alleged improvements, any alleged benefits of the invention are at best, an improvement to the abstract idea of rules or instructions followed to collect data, analyze the collected data, and output relevant data based on the analysis accordingly. However, an improved abstract idea is still an abstract idea and the claims do not provide a technical improvement.
Furthermore, the computing system did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. Applicant’s claims do not recite the invention of improvements to computer functionality, technology, or any other technological field, but the use of generic computer components (i.e., a computing system having a processor, memory storing computer-executable instructions) to collect data, analyze the collected data, and output relevant data based on the analysis accordingly, which is an abstract idea, but for the recitation of generic computer components. While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement to computer technology, a physical improvement to the computer, or any other technical improvement. See MPEP § 2106.04(d)(1) and 2106.05(a).
Applicant argues “independent claims 1, 12, and 1 further recite an ordered combination of features that is not well-understood, routine, or conventional and are thus patent eligible… The lack of novelty and obviousness rejections demonstrate that the claims of the present application are not well-understood, routine, or conventional, and the Examiner provides no evidence (and thus insufficient support) that the recited elements (individually or combination) were widely prevalent or in common use in the relevant industry.” However, Applicant fails to specify the “ordered combination of features that is not well-understood, routine, or conventional” and how they are “patent eligible.” Regardless, whether the elements define only well-understood, routine, conventional activity is not a standalone test for determining eligibility, but an exemplary consideration in a non-limiting list of considerations. Furthermore, per MPEP § 2106.05(I): “the search for an inventive concept should not be confused with a novelty or non-obviousness determination…As made clear by the courts, the "‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter…a claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty…Because [novelty and obviousness] are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101.”
Thus, the claim as a whole does not amount to significantly more than the judicial exception.
Thus, Examiner maintains the 101 rejections of claims 1-20, which have been updated to address Applicant’s amendments and remarks and to comply with the 2019 Revised Patent Subject Matter Eligibility Guidance in the above Office Action and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence in the above Office Action.
Conclusion
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 extension fee 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 date of this final action.
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/EMILY HUYNH/Primary Examiner, Art Unit 3683
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