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 .
Response to Preliminary Amendment
In the preliminary amendment filed on February 28, 2025, the following has occurred: claim(s) 1 have been amended and claim(s) 2-20 have been added. Now, claim(s) 1-20 are pending.
Claim Objections
Claim 1 objected to because of the following informalities: “the first physiological patient variables;” in p. 2, ll. 9, “a spectral coherence” in p. 2, ll. 16-17, “the one or both of the diagnoses and the prediction” in p. 2, ll. 23-24. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the first set of physiological patient variables”, “the spectral coherence”, “the one or both of the diagnoses and the prediction of the adverse cardiovascular event”.
Claim 2 objected to because of the following informalities: “log-return time series,” in p. 3, ll. 15-16, “the at least one set of time series measurements” in p. 3, ll. 16. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the log-return time-series”, “the at least one set of time-series measurements”.
Claim 7 objected to because of the following informalities: “log-return time series,” in p. 4, ll. 9. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the log-return time-series”.
Claim 8 objected to because of the following informalities: “the first physiological patient variables;” in p. 4, ll. 19, “a spectral coherence” in p. 4, ll. 24-25, “the one or both of the diagnoses and the prediction” in p. 5, ll. 6-7. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the first set of physiological patient variables”, “the spectral coherence”, “the one or both of the diagnoses and the prediction of the adverse cardiovascular event”.
Claim 9 objected to because of the following informalities: “log-return time series,” in p. 5, ll. 9, “the at least one set of time series measurements” in p. 5, ll. 9. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the log-return time-series”, “the at least one set of time-series measurements”.
Claim 14 objected to because of the following informalities: “the first physiological patient variables;” in p. 6, ll. 9, “a spectral coherence” in p. 6, ll. 16-17, “the one or both of the diagnoses and the prediction” in p. 6, ll. 25-26. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the first set of physiological patient variables”, “the spectral coherence”, “the one or both of the diagnoses and the prediction of the adverse cardiovascular event”.
Claim 15 objected to because of the following informalities: “log-return time series,” in p. 6, ll. 28, “the at least one set of time series measurements” in p. 6, ll. 28-29. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the log-return time-series”, “the at least one set of time-series measurements”.
Claim 20 objected to because of the following informalities: “log-return time series,” in p. 7, ll. 19. These appear to be typographical errors. Appropriate correction is required. For examination purposes, the Examiner will interpret the claimed portion as “the log-return time-series”.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-7: Step 2A Prong One
collect a set of measurements of: a set of first physiological patient variables and a set of second physiological patient variables that differ from the set of first physiological patient variables;
based on the set of measurements, constructing at least one set of time-series measurements representing measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps;
determining, based on the set of time-series measurements and a transform selected from a group comprising a Fourier transform and a wavelet transform, a transfer entropy and a spectral coherence;
generating a set of ischemia condition data based on the transfer entropy and the spectral coherence;
automatically creating, based at least in part on the set of ischemia condition data, clinical information indicating one or both of a diagnoses and a prediction for an adverse cardiovascular event; and
electronically writing, encoded data, wherein the encoded data corresponds at least partially to the clinical information indicating the one or both of the diagnoses and the prediction for the adverse cardiovascular event
These limitations, as drafted, given the broadest reasonable interpretation, managing
personal behavior or relationships or interactions between people (including social activities,
teaching, and following rules or instructions) that constitute Certain Methods of Organizing Human Activity, but for the recitation of generic computer components and generally linking the abstract idea to a technical environment. That is, other than reciting “one or more hardware processors”, “utilizing a measurement device, associated with a patient and with an electronic digital memory at a medical records computer system, to”, “via the one or more hardware processors and”, “via the one or more hardware processors,”, “to the electronic digital memory at the medical records computer system” to perform these functions, nothing in the claim precludes the limitations from practically being performed by a human following rules or instructions. For example, but for the “one or more hardware processors”, “utilizing a measurement device, associated with a patient and with an electronic digital memory at a medical records computer system, to” language, the “collect” function in the context of this claim encompasses a user following instructions to collect a set of measurements of a patient. Similarly, but for the “one or more hardware processors” language, the “constructing” function in the context of this claim encompasses a user following instructions to determine at least one set of time-series measurements representing measurement values. Similarly, but for the “one or more hardware processors” language, the “determining” and “generating” functions in the context of this claim encompasses a user following instructions to determine a transfer entropy and spectral coherence, and determine a set of ischemia condition data. Finally, but for the “via the one or more hardware processors,”, “to the electronic digital memory at the medical records computer system” language, the “creating” and “writing” functions in the context of this claim encompasses a user following instructions to determining a diagnoses and/or a prediction for an adverse cardiovascular event, and storing the diagnoses and/or the prediction for an adverse cardiovascular event in a medical records system. The claims recite steps that could be accomplished by a physician, doctor, or nurse following instructions to determine a diagnoses and/or a prediction for an adverse cardiovascular event. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people of the limitation but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, these claims recite an abstract idea.
Claims 2-7 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea. For example, claims 2-4 include the abstract idea identified above and further describe the determination of the transfer entropy and the spectral coherence, and determining a composite index. Similarly, claim 5 includes the abstract idea identified above and further describes the wavelet transform. Similarly, claim 6 includes the abstract idea identified above and further describes the constructing step and the Fourier transform. Finally, claim 7 include the abstract idea identified above and describes presence, likelihood, or risk of inflammation, and accessing a stored arterial anatomy measurement. Therefore, these claims recite limitations that fall into the Certain Methods of Organizing Human Activity grouping of abstract ideas.
Claims 1-7: Step 2A Prong
This judicial exception is not integrated into a practical application because the remaining elements amount to no more than general purpose computer components programmed to perform the abstract idea and generally linking the abstract idea to a technical environment.
This judicial exception is not integrated into a practical application because the “one or more hardware processors”, “an electronic digital memory at a medical records computer system”, “a measurement device”, to the electronic digital memory at the medical records computer system” are recited at a high-level of generality. As set forth in the MPEP 2106.04(d) "merely including instructions to implement an abstract idea on a computer" is an example of when an abstract idea has not been integrated into a practical application.
Additionally, the claims recite “utilizing a measurement device, associated with a patient”, “via the one or more hardware processors and”, “via the one or more hardware processors,” at a high degree of generality, amount no more than generally linking the abstract idea to a particular technical environment. The recitation is also similar to adding the words “apply it” to the abstract idea. As set forth in MPEP 2106.05(f), merely reciting the words “apply it” or an equivalent, is an example of when an abstract idea has not been integrated into a practical application.
Claims 1-7: Step 2B
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 integration of
the abstract idea into a practical application, the additional element of using a computer configured to perform above identified functions amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Alice 573 U.S. at 223 ("mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.")
Additionally, generally linking the abstract idea to a particular technological environment
does not amount to significantly more than the abstract idea (See MPEP 2106.05(h) and Affinity
Labs of Texas v. DirectTV, LLC, 838 F.3d 1253, 120 USP12d 1201 (Fed. Cir. 2016)). The claims are not patent eligible.
Claim(s) 8-13 mirror claims 1-6 only within computer-implemented method form, and are rejected for the same reason as claims 1-6.
Claims 14-20 mirror claims 1-7 only within non-transitory media form, and are rejected for the same reason as claims 1-7.
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 (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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan et al. (U.S. Patent Pre-Grant Publication No. 2019/0216350)) in view of Moorman et al. (U.S. Patent Pre-Grant Publication No. 2016/0143594).
As per independent claim 1, Sullivan discloses a system having one or more hardware processors configured to facilitate a plurality of operations, the operations comprising:
utilizing a measurement device, associated with a patient and with an electronic digital memory at a medical records computer system, to collect a set of measurements (See [0259]-[0261], [0426]: A medical support device may include sensors for monitoring parameters of a subject to estimate the risk of a medical event occurring, which the Examiner is interpreting the databases of collected subject data and associated results to encompass an electronic digital memory at a medical records computer system, interpreting a medical support device to encompass a measurement device, interpreting monitoring parameters of a subject to encompass collect a set of measurements) of: a set of first physiological patient variables and a set of second physiological patient variables that differ from the set of first physiological patient variables (See [0175], [0276]: Acquiring a first set of physiological information of a subject received during a first period of time and based at least in part on a first ECG signal of the subject, and a second set of physiological information of the subject received during a second period of time, which the Examiner is interpreting a second set of physiological information to encompass a set of second physiological patient variables that differ from the set of first physiological patient variables as the physiological parameters can be one or more parameters associated with the subject's ECG or EEG, blood pressure, heart rate or change in heart rate, etc. ([0276]));
based on the set of measurements, constructing at least one set of time-series measurements representing measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps (See [0332]-[0334]: The time series data for each patient can be evaluated using a number of techniques to assess whether the patient's risk is increasing or decreasing over time, which the Examiner is interpreting the time series data for each patient to encompass at least one set of time-series measurements representing measurement values);
generating a set of ischemia condition data based on the transfer entropy and the spectral coherence (See [0230]: An event estimation of risk score can be determined for any combination of such cardiac events, which the Examiner is interpreting an event estimation of risk score to encompass a set of ischemia condition data when combined with Moorman's disclosure of frequency spectra and cross-correlation);
automatically creating, via the one or more hardware processors and based at least in part on the set of ischemia condition data, clinical information indicating one or both of a diagnoses and a prediction for an adverse cardiovascular event (See [0221], [0258]: Automatically analyzing subject data to predict conditions including medical events, for example, adverse cardiac events, which the Examiner is interpreting predict conditions to include one or both of a diagnoses and a prediction for an adverse cardiovascular event, and interpreting risk scores to encompass the set of ischemia condition data); and
electronically writing, via the one or more hardware processors, encoded data to the electronic digital memory at the medical records computer system, wherein the encoded data corresponds at least partially to the clinical information indicating the one or both of the diagnoses and the prediction for the adverse cardiovascular event (See [0264], [0304]: The calculated event estimation of risk scores as a function of time are stored (e.g., by the control unit 120), event estimation of risk scores (e.g., which can include both criticality and confidence measures) are stored for each of the time periods and each of the medical events for which the score is calculated, which the Examiner is interpreting to encompass the claimed portion as a memory unit and processor is utilized to store subject information.)
While Sullivan teaches a system for constructing at least one set of time-series measurements representing measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps, Sullivan may not explicitly teach determining, based on the set of time-series measurements and a transform selected from a group comprising a Fourier transform and a wavelet transform, a transfer entropy and a spectral coherence.
Moorman teaches a system for determining, based on the set of time-series measurements and a transform selected from a group comprising a Fourier transform and a wavelet transform, a transfer entropy and a spectral coherence (See [0052]: Calculating mathematical characteristics of the relationships of one or more simultaneous time series in several domains using univariate measures and cross-measures including but not limited to the time-domain (e.g., autocorrelation, cross-correlation and covariance), frequency domain (e.g., frequency spectra using Fourier transform, Lomb periodogram or other techniques, cross-spectra, coherence, transfer functions), wavelet domain (e.g., cross-wavelet transform), non-linear domain (e.g., cross-entropy), phase domain (e.g., Hilbert transform), information domain (Granger causality and mutual information), and other mathematical and statistical domains using traditional or novel analyses, transforms, estimators or other mathematical calculations, which the Examiner is interpreting the frequency spectra to encompass spectral coherence, interpreting the cross-correlation to encompass a transfer entropy, and interpreting the cross-wavelet transform to encompass a wavelet transform.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include determining, based on the set of time-series measurements and a transform selected from a group comprising a Fourier transform and a wavelet transform, a transfer entropy and a spectral coherence as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 8 and 14 mirror claim 1 only within different statutory categories, and are rejected for the same reasons as claim 1.
As per claim 2, Sullivan/Moorman discloses the system of claim 1 as described above. Sullivan may not explicitly teach wherein the operations further comprise creating at least one log-return time-series, using the at least one set of time-series measurements, to determine one or both of the transfer entropy and the spectral coherence.
Moorman teaches a system wherein the operations further comprise creating at least one log-return time-series, using the at least one set of time-series measurements, to determine one or both of the transfer entropy and the spectral coherence (See [0183]-[0184], [0295]: Multivariate statistical methods, such as logistic regression (this is the basis of the HRC index for the NICU)(49, 52, 81), k nearest neighbor analysis (58), neural nets, and other techniques can be used for early diagnosis of neonatal sepsis with the analysis of clinical and heart rate characteristics, which the Examiner is interpreting the logistic regression to encompass at least one log-return time-series.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include the operations further comprise creating at least one log-return time-series, using the at least one set of time-series measurements, to determine one or both of the transfer entropy and the spectral coherence as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 9 and 15 mirror claim 2 only within different statutory categories, and are rejected for the same reasons as claim 2.
As per claim 3, Sullivan/Moorman discloses the system of claim 1 as described above. Sullivan may not explicitly teach wherein the operations further comprise utilizing a log-return time-series to determine the transfer entropy and the spectral coherence and generating a composite index for an ischemic event based on the transfer entropy and the spectral coherence.
Moorman teaches a system wherein the operations further comprise utilizing a log-return time-series to determine the transfer entropy and the spectral coherence and generating a composite index for an ischemic event based on the transfer entropy and the spectral coherence (See [0183]-[0184], [0295]: Multivariate statistical methods, such as logistic regression (this is the basis of the HRC index for the NICU)(49, 52, 81), k nearest neighbor analysis (58), neural nets, and other techniques can be used for early diagnosis of neonatal sepsis with the analysis of clinical and heart rate characteristics, which the Examiner is interpreting the heart rate characteristic (HRC) index to encompass a composite index for an ischemic event.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include the operations further comprise utilizing a log-return time-series to determine the transfer entropy and the spectral coherence and generating a composite index for an ischemic event based on the transfer entropy and the spectral coherence as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 10 and 16 mirror claim 3 only within different statutory categories, and are rejected for the same reasons as claim 3.
As per claim 4, Sullivan/Moorman discloses the system of claims 1 and 3 as described above. Sullivan further teaches wherein the operations further comprise evaluating the composite index against a threshold associated with one or both of a first physiological patient parameter and a second physiological patient parameter (See [0305]-[0306]: The event estimation of risk scores for each of the calculated time periods are compared to event thresholds, such as stored event estimation of risk threshold values, which the Examiner is interpreting the event thresholds to encompass a threshold associated with one or both of a first physiological patient parameter and a second physiological patient parameter, and interpreting the event estimation of risk scores to encompass the composite index when combined with Moorman.)
Claim(s) 11 and 17 mirror claim 4 only within different statutory categories, and are rejected for the same reasons as claim 4.
As per claim 5, Sullivan/Moorman discloses the system of claim 1 as described above. Sullivan may not explicitly teach wherein the wavelet transform is applied to data associated with the patient to determine a particular spectral coherence that is utilized to predict a level of patient risk for coronary artery disease.
Moorman teaches a system wherein the wavelet transform is applied to data associated with the patient to determine a particular spectral coherence that is utilized to predict a level of patient risk for coronary artery disease (See [0052], [0230]-[0232]: Detecting abnormal entrainment of waveform and vital sign time series representations of physiological processes may be implemented , which the Examiner is interpreting the frequency spectra to encompass a particular spectral coherence to predict a level of patient risk for coronary artery disease when combined with Sullivan's disclosure of event estimation of risk threshold values.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include the wavelet transform is applied to data associated with the patient to determine a particular spectral coherence that is utilized to predict a level of patient risk for coronary artery disease as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 12 and 18 mirror claim 5 only within different statutory categories, and are rejected for the same reasons as claim 5.
As per claim 6, Sullivan/Moorman discloses the system of claim 1 as described above. Sullivan further teaches wherein the constructing corresponds to combining the set of measurements with a first set of data, wherein the at least one set of time-series measurements represents measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps (See [0332]-[0334]: The time series data for each patient can be evaluated using a number of techniques to assess whether the patient's risk is increasing or decreasing over time, which the Examiner is interpreting the time series data for each patient to encompass at least one set of time-series measurements representing measurement values), and wherein the Fourier transform is applied to data associated with an electronic patient record to determine a particular spectral coherence that is utilized to predict a level of patient risk for stroke.
While Sullivan teaches a system wherein the constructing corresponds to combining the set of measurements with a first set of data, wherein the at least one set of time-series measurements represents measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps,
Sullivan may not explicitly teach wherein the Fourier transform is applied to data associated with an electronic patient record to determine a particular spectral coherence that is utilized to predict a level of patient risk for stroke.
Moorman teaches a system wherein the constructing corresponds to combining the set of measurements with a first set of data, wherein the at least one set of time-series measurements represents measurement values, of the set of first physiological patient variables and of the set of second physiological patient variables, at corresponding date-time stamps, and wherein the Fourier transform is applied to data associated with an electronic patient record to determine a particular spectral coherence that is utilized to predict a level of patient risk for stroke (See [0052], [0230]-[0232]: Detecting abnormal entrainment of waveform and vital sign time series representations of physiological processes may be implemented , which the Examiner is interpreting the frequency spectra to encompass a particular spectral coherence to predict a level of patient risk for stroke when combined with Sullivan's disclosure of event estimation of risk threshold values.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include the Fourier transform is applied to data associated with an electronic patient record to determine a particular spectral coherence that is utilized to predict a level of patient risk for stroke as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 13 and 19 mirror claim 6 only within different statutory categories, and are rejected for the same reasons as claim 6.
As per claim 7, Sullivan/Moorman discloses the system of claim 1 as described above. Sullivan further teaches wherein one or both of the transfer entropy and the spectral coherence are determined based on a log-return time-series, and wherein the clinical information (a) further indicates that one or more of a presence, likelihood, or risk of inflammation that is endothelial in origin is associated with the patient, and
(b) is generated automatically via the one or more hardware processors without accessing by the one or more hardware processors a stored arterial anatomy measurement created using an invasive or imaging modality by the one or more hardware processors (See [0275]-[0277]:The event estimation of risk score may be calculated based on one or more measured physiological parameters of the subject, for example, one or more parameters associated with the subject's ECG or EEG, blood pressure, heart rate or change in heart rate, tidal CO.sub.2, SpO.sub.2, SMO.sub.2, cerebral blood flow, brain oxygen level, tissue pH, reaction of the subject's heart to tilting of the subject, and/or ultrasound images of the subject's heart, which the Examiner is interpreting the ultrasound images of the subject's heart to encompass a stored arterial anatomy measurement created using an invasive or imaging modality by the one or more hardware processors as the information may be stored in a memory of the base unit.)
While Sullivan teaches a system (b) is generated automatically via the one or more hardware processors without accessing by the one or more hardware processors a stored arterial anatomy measurement created using an invasive or imaging modality by the one or more hardware processors,
Sullivan may not explicitly teach wherein one or both of the transfer entropy and the spectral coherence are determined based on a log-return time-series, and wherein the clinical information (a) further indicates that one or more of a presence, likelihood, or risk of inflammation that is endothelial in origin is associated with the patient.
Moorman teaches a system wherein one or both of the transfer entropy and the spectral coherence are determined based on a log-return time-series (See [0183]-[0184], [0295]: Multivariate statistical methods, such as logistic regression (this is the basis of the HRC index for the NICU)(49, 52, 81), k nearest neighbor analysis (58), neural nets, and other techniques can be used for early diagnosis of neonatal sepsis with the analysis of clinical and heart rate characteristics, which the Examiner is interpreting the logistic regression to encompass one or both of the transfer entropy and the spectral coherence are determined based on a log-return time-series), and wherein the clinical information (a) further indicates that one or more of a presence, likelihood, or risk of inflammation that is endothelial in origin is associated with the patient (See [0108]-[0110]: Heart failure has an inflammatory footprint (68), and a current view is that unchecked cytokine production mediated by NK-kappaB promotes apoptosis and adverse cardiac remodeling (69, 70), which the Examiner is interpreting the identification of an inflammatory footprint to encompass inflammation that is endothelial in origin is associated with the patient when combined with Sullivan's disclosure of event estimation of risk threshold values), and
(b) is generated automatically via the one or more hardware processors without accessing by the one or more hardware processors a stored arterial anatomy measurement created using an invasive or imaging modality by the one or more hardware processors.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed to modify the system of Sullivan to include one or both of the transfer entropy and the spectral coherence are determined based on a log-return time-series, and wherein the clinical information (a) further indicates that one or more of a presence, likelihood, or risk of inflammation that is endothelial in origin is associated with the patient as taught by Moorman. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Sullivan with Moorman with the motivation of allowing earlier diagnosis and therapy (See Background of the Invention of Moorman in Paragraph [0003]).
Claim(s) 20 mirrors claim 7 only within a different statutory category, and is rejected for the same reasons as claim 7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Stahmann et al. (U.S. Patent Pre-Grant Publication No. 2004/0133247), describes a cardiac device in which heart rate variability is computed in order to detect changes indicative of cardiac ischemia.
Teixeira (U.S. Patent Pre-Grant Publication No. 2012/0022384), describes a probabilistic digital signal processor is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and/or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater.
Wexler et al. (“Brachial artery reactivity in patients with severe sepsis: an observational study”), describes brachial artery hyperemic velocity may be a useful measurement to identify patients who could benefit from novel therapies designed to reverse microvascular dysfunction in severe sepsis and to assess the physiologic efficacy of these treatments.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bennett S Erickson whose telephone number is (571)270-3690. 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, Robert Morgan can be reached at (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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/Bennett Stephen Erickson/Primary Examiner, Art Unit 3683