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 .
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 (i.e., changing from AIA to pre-AIA ) 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.
Response to Amendment
In the amendment dated 8/14/2025, the following has occurred: Claims 1, 5, and 9 have been amended; Claims 14, 15, 17, 18, 21, and 22 have been canceled; Claims 23 and 24 have been added..
Claims 19 and 20 have been previously canceled.
Claims 1 – 13, 16, 23, and 24 are pending.
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 – 13, 16, 23, and 24 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.
The claims, understood as whole, recite(s) subject matter within a statutory category as a machine (claims 1 – 4, 13, and 23), process (claims 5 – 8, 16, and 24), and manufacture (claims 9 – 12) which recite the abstract idea steps of
database of participant symptom data;
receive from participants their symptom data, and
display the data views associated with participant symptom data content as visualizations; and
capture self-reported participant symptom data from individual participants and track changes in their reported symptoms over time; and
query the received participant symptom data, to identify patterns in the data indicative of participant clusters and episodes indicative of possible illness, which information can then be used to respond to investigative queries, including:
identify participant clusters and episodes within a stream of the participant symptom data, as defined by the one or more data views; and
reporting such participant clusters and episodes
These steps of claims 1 – 13, 16, 23, and 24, as drafted, under the broadest reasonable interpretation, includes performance of the limitation in the mind but for recitation of generic computer components. That is, other than reciting steps as performed by the generic computer components, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the computing system language, providing access to a data warehouse in the context of this claim encompasses a mental process of the user. Similarly, the limitation of a presentation layer, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, but for the computing system language, querying in the context of this claim encompasses a mental process of the user. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
These steps of claims 1 – 13, 16, 23, and 24, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. The Examiner makes this understanding of the claims, as a whole, in view of the specification. In particular, the Examiner understands that the invention is used to overcome this problem:
[0003] For example, when participation is voluntary, there may be no requirement that a person exhibiting symptoms, or who has been tested for the presence of a particular medical condition, will actually return to report any change in their symptoms, which information might be useful in treatment of their condition, or tracing within the wider community. Voluntary and/or intermittent reporting may also impact the ability to accurately assess a particular patient's progress over a period of time
The problem is solved using:
Summary:
[0004] In accordance with an embodiment, described herein are systems and methods for use of data analytics in medical applications, including the use of pattern detection in assessing self-reported participant symptom data indicative of possible illness. A patient monitoring system or service can be provided, for example at an analytics cloud environment. The system is adapted to capture self-reported participant symptom data from individual participants, and track changes in their reported symptoms over time. The system performs data queries against the received participant symptom data, to identify patterns in the data indicative of participant clusters and episodes indicative of possible illness, which information can then be provided, for example, to a medical organization system and used to respond to investigative queries. The approach can accommodate voluntary and/or intermittent reporting, including sparsity or gaps in the input stream of symptom data received from the participants.
The result is that the abstract idea is applied to technology and is not a technological improvement. The invention does not have a practical application as the resultant data has only a potential usage.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2 – 4, 6 – 8, 10 – 13, 16, 23, and 24, reciting particular aspects of how identifying patterns may be performed in the mind but for recitation of generic computer components).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of a computer system providing amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of receive from the participants amounts to mere data gathering, recitation of queries amounts to selecting a particular data source or type of data to be manipulated, recitation of reporting such participant clusters amounts to insignificant application, see MPEP 2106.05(g))
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2 – 4, 6 – 8, 10 – 13, 16, 23, and 24, additional limitations which amount to invoking computers as a tool to perform the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as claims 1 – 13, 16, 23, and 24; self-reporting and receiving, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); track changes, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii);
Additional Elements:
Computer system – paragraphs 30, 31
Data warehouse – paragraph 38
a presentation layer/ interface – paragraph 91 and figure 4, #324 - #346, #242
patient monitoring service – paragraphs 48 and 49
interface/ dashboard – web browser column 33, lines 29 – 38
data model – only found in paragraph 33 as, “In accordance with an embodiment, the data transformation layer can include a data model, such as, for example, a knowledge model (KM), or other type of data model, that the system uses to transform the transactional data, into a model format understood by the analytics cloud environment. The model format can be provided in any data format suited for storage in a data warehouse.”
Data query – various instances of “MATCH_RECOGNIZE” such as paragraph 91
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2 – 4, 6 – 8, 10 – 13, 16, 23, and 24, additional limitations which amount to elements that have been recognized as electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1 – 13 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Jain et al., U.S. Patent 11/456,080 in view of Jain et al,. U.S. Pre-Grant Publication 2012/0072455.
The Examiner notes that the two Jain’s are different people and that the ‘455 Jain is an Oracle employee.
As per claim 1,
Jain ‘080 teaches a system comprising:
a computer system comprising (figure 1, #110)
one or more processor and memory (column 27, lines 36 – 49 server, column 132 lines 47 – 67 memory description),
said computer system providing access to a data warehouse for storage of a participant symptom data (figure 1,#120 data storage, and column 28, lines 27 – 45 module #112 a module 112 includes software or configuration data to direct data collection and reporting and interactions with the user.)
said computer system further comprising
a data model that the system uses to transform transactional data into a model format understood by the system (column 52, lines 13 – 25 database with structure to make available as under or column 57, lines 24 – 41 captured in rules, look-up tables, databases..); and
a presentation layer that enables access to data content stored at a data warehouse instance via one or more dashboards that displays data views (column 30, lines 23 – 53 #112a module appropriate for the user , column 31 lines 13 - – The figures 12 and 13 are described as dashboards within the specification. Figures 12 and 13 are only examples); and
a patient monitoring system provided at the computer system and operating as a service that includes a first interface, and a second interface (figure 1 and column 30, lines 29 – 53 electronic, column 40, lines 25 – 49 survey answers),
said first interface, operating as a participant interface (It should be understood that “operating as” is a descriptive label and not a function that is performed. It is a description of an intended use), in communication with a plurality of participant devices that include a participant reporting application and that are adapted to receive from participants the participant symptom data (figure 1, #106a Survey Responses)
wherein each participant device communicates with the first interface of the system to provide the participant symptom data to the patent monitoring system (figure 1, #102a…#102b column 27, line 63 – column 28, line 16 users column 29 lines 5 – 32 modules)
wherein the participant symptom data is stored in a database at the data warehouse instance for subsequent use in performing the data queries (column 24, line 65 decentralized databases and column 132 lines 15 and 16 database management system– “for subsequent use describes); and
said second interface, operating as a provider interface (as described in the first interface), in communication with one or more provider systems that display the data views associated with the participant symptom data content as visualizations (figure 1, #106a sensor data, physiological measurements – It should be emphasized that the second interface data is only captured and reported. The data is never claimed to be processed);
wherein the one or more provider systems communicate with the provider interface to receive or access the participant symptom data (figure 1, #102a…#102b column 27, line 63 – column 28, line 16 users column 29 lines 5 – 32 modules)
wherein a provider system includes a user interface that displays a dashboard of information or visualizations associated with the participant symptom data (figure 12);
wherein the system includes one or more cluster pattern definitions, for use by the system in performing data queries against the received participant symptom data as defined by a cluster pattern, to determine participant clusters (column 35 lines 22 – line 58 marker definitions to indicate or predict disease-related factors column 57, lines 24 – 41 look-up tables Specification paragraph 90);
wherein the patient monitoring system operates to capture the participant symptom data from individual participants, via the participant devices communicating with the first interface, and track changes in their reported symptoms over time (column 2, liens 9 – 23 monitoring data and column 5, lines 16 – 50 monitoring survey data) ; and
wherein the system performs data queries against the participant symptom data received from the plurality of participant devices via the first interface of the patient monitoring system, to identify patterns in the data indicative of participant clusters and episodes(column 35, line – column 36, line 15 and column 34, line 63 – column 35 lines 22, column 61 lines 42 – 67 clustering), which information can then be used to respond to investigative queries (column 41, lines 43 – 59 research) , including:
processing one or recognize data queries within a rolling window (column 52, lines 55 updated as additional information comes in) of data associated with a stream of the participant symptom data to identify participant clusters and episodes within the stream of the participant symptom data, as defined by the one or more data views (column 91, line 27 – column 92, line 12 – it should be noted that “data views” are not limited by the Specification to be anything. Figure 2 and paragraph 39 includes, “Disease specific data views 306” but this does not explain what is required); and
reporting such participant clusters and episodes, as identified within the stream of the participant symptom data, via the and second interface of the patient monitoring system, to the one or more provider systems (figure 17 and column 93, lines 7 – 25 a map).
Jain ‘080 does not explicitly show “query”. However, Jain ‘080 does teaches in column 133, line 66 to column 134, line 5:
In each instance where an HTML file is mentioned, other file types or formats may be substituted. For instance, an HTML file may be replaced by an XML, JSON, plain text, or other types of files. Moreover, where a table or hash table is mentioned, other data structures (such as spreadsheets, relational databases, or structured files) may be used.
Jain ‘455 includes within paragraph 74, “In one embodiment, a programming language
such as SQL, which is commonly used to query databases, may be used.
Jain ‘080 does not explicitly teach the system
processing one or more SQL data queries that correspond to one or more defined cluster patterns, including one or more pattern-matching SQL data queries that incorporate a match recognition clause, within a rolling window of data associated with a stream of the participant symptom data, as configured by a data view, to identify participant clusters and episodes within the stream of the participant symptom data, as defined by the one or more data views; and
reporting such participant clusters and episodes, as identified within the stream of the participant symptom data, via the second interface of the patient monitoring system, to the one or more provider systems wherein the provider system displays a dashboard of information or visualizations associated with the participant clusters and episodes.
Jain ‘455 further teaches the system
processing one or more data queries (figure 2A #205 - #215 and paragraphs 73 - 76)
that correspond to one or more defined cluster patterns (paragraph 73, regular expression or paragraph 74 pattern to be matched),
including one or more pattern-matching SQL data queries that incorporate a match recognition clause (paragraphs 74 – 76),
within a rolling window of data associated with a stream of the participant symptom data (paragraph 4 Continuous Query Language to process event streams),
as configured by a data view (paragraphs 5, 54 – 61),
to identify participant clusters and episodes within the stream of the participant symptom data (paragraph 76 pattern matching),
as defined by the one or more data views (paragraph 76 and 77); and
reporting such participant clusters and episodes, as identified within the stream of the participant symptom data, via the second interface of the patient monitoring system, to the one or more provider systems. wherein the provider system displays a dashboard of information or visualizations associated with the participant clusters and episodes (figure 6).
It would have been obvious to one of ordinary skill in the art before the effective filing date to add these features into Jain ‘080. One of ordinary skill in the art before the effective filing date would have added these features into Jain ‘080 with the motivation to use a common method to query databases.
As per claim 2, Jain ‘080 in view of Jain ‘455 teaches the system of claim 1 as described above.
Jain ’080 further teaches the system wherein the patient monitoring service is provided at a cloud environment and accessed as a service via one or more participant interfaces or provider interfaces (figure 1 and column 77, lines 1 – 25 Internet).
As per claim 3, Jain ‘080 in view of Jain ‘455 teaches the system of claim 1 as described above.
Jain ’080 does not explicitly teach however Jain ‘455 further teaches the system wherein the data queries include MATCH_RECOGNIZE data queries that the system performs against the received participant symptom data, to identify patterns in the data (paragraph 70).
It would have been obvious to one of ordinary skill in the art before the effective filing date to add these features into Jain ‘080 for the reasons as described above.
As per claim 4, Jain ‘080 in view of Jain ‘455 teaches the system of claim 1 as described above.
Jain ’080 further teaches the system wherein the participant interface enables communication with mobile devices or other devices that include a participant reporting application and that are adapted receive from participants a symptom data via a survey (figure 1).
As per claim 5,
Jain ‘080 in view of Jain ‘455 teaches a method as described above in claim 1.
As per claim 6, Jain ‘080 in view of Jain ‘455 teaches the method of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the method as described above in claim 2.
As per claim 7, Jain ‘080 in view of Jain ‘455 teaches the method of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the method as described above in claim 3.
As per claim 8, Jain ‘080 in view of Jain ‘455 teaches the method of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the method as described above in claim 4.
As per claim 9,
Jain ‘080 in view of Jain ‘455 teaches a non-transitory computer readable storage medium, including instructions stored thereon which when read and executed by one or more computers cause the one or more computers to perform a method as described above in claim 1.
As per claim 10, Jain ‘080 in view of Jain ‘455 teaches the medium of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the medium as described above in claim 2.
As per claim 11, Jain ‘080 in view of Jain ‘455 teaches the medium of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the medium as described above in claim 3.
As per claim 12, Jain ‘080 in view of Jain ‘455 teaches the medium of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the medium as described above in claim 4.
As per claim 13, Jain ‘080 in view of Jain ‘455 teaches the system of claim 1 as described above.
Jain ’080 does not explicitly teach however Jain ‘455 further teaches the system wherein the system performs pattern-matching in a sequence of rows of data as an incremental process, with one row after another examined to see if it fits the pattern (paragraphs 72 and 75).
It would have been obvious to one of ordinary skill in the art before the effective filing date to add these features into Jain ‘080 for the reasons as described above.
As per claim 16, Jain ‘080 in view of Jain ‘455 teaches the method of claim 5 as described above.
Jain ‘080 in view of Jain ‘455 further teaches the method as described above in claim 13.
As per claim 23, Jain ‘080 in view of Jain ‘455 teaches the system of claim 1 as described above.
Jain ‘080 further teaches the system:
wherein the system receives the participant symptom data from the participants via mobile devices that includes a participant reporting application and user interface which provides displays or otherwise provides access to a survey which the participant complete, to provide their participant symptom data (figure 1 #104a or #107a and column 27 line 63 – column 28, line 16);
wherein each participant device communicates with the participant interface of the system via the Internet or other communication means to provide self-reported participant symptom data (column 77, lines 1 – 25 user devices connects via the internet or public or private network);
wherein the results of surveys are accessible using a medical organization system having a device hardware, dashboard application, and user interface that enables display of a dashboard of information that allows interactive reporting or visualizations (figure 11, #1102 and #1104 with predictions #1120 and column 71, lines 27 – 51; and
wherein the medical organization system communicates with the provider interface of the system, via the Internet or other communication means of receiving or accessing the self-reported participant symptom data (figure 11 network).
As per claim 24, Jain ‘080 in view of Jain ‘455 teaches the method of claim 5 as described above.
Jain ‘080 further teaches the method as described above in claim 23.
Response to Arguments
Applicant's arguments filed 8/14/2025 have been fully considered but they are not persuasive.
IV. Claim Rejections under 35 U.S.C. §101
The Applicant states, “Applicant respectfully submits that the claims, as currently amended, conform with the requirements of 35 U.S.C. 101. Reconsideration thereof is respectfully requested.” Please see the updated rejection above.
V. Claim Rejections under 35 U.S.C. §103
The Applicant states, “neither Jain '080 nor Jain '455 appear to describe, for example, wherein a patient monitoring system operating as a service includes a first interface in communication with a plurality of participant devices that include a participant reporting application and …” Please see the updated rejections above.
The Applicant states, “In view of the above remarks, Applicant respectfully submits that Claim 1, as currently amended, is neither anticipated by, nor obvious in view of the cited references, when considered alone or in combination. Reconsideration thereof is respectfully requested.” The Applicant’s opinion is noted. Please see the updated rejections above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shetty et al Pub. No.: US 2022/0160310 This disclosure is directed to techniques for recording and recognizing physiological parameter patterns associated with symptoms
Sabeti et al., Pub. No.: US 2021/0050116 The technology uses aggregated health data and outbreak models to conduct differential diagnosis and provide risk assessments that indicate a likelihood of contracting COVID-19.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Neal R Sereboff whose telephone number is (571)270-1373. The examiner can normally be reached M - T, M - F 8AM - 6PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached on (571)272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NEAL SEREBOFF/
Primary Examiner
Art Unit 3626