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 .
Status
Claims 1-20 have been examined. Claims 1, 11 have been amended. Claims 6-7, 16-17 have been canceled.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11154240. Although the claims at issue are not identical, they are not patentably distinct from each other because both claims recite “training a machine-learning model using the first training data set and the second training data set; and generating the diagnostic output by determining at least a prognostic label associated with the diagnostic output …”.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11937939. Although the claims at issue are not identical, they are not patentably distinct from each other because both claims recite “training a machine-learning model using the first training data set and the second training data set; and generating the diagnostic output by determining at least a prognostic label associated with the diagnostic output …”.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter.
Claim 1 is directed towards a system for utilizing diagnostics for informed vibrant constitutional guidance, the system comprising:
at least a server;
a diagnostic engine operating on the at least a server, wherein the diagnostic engine is configured to:
receive a first set of contextual information associated with a user;
generate a diagnostic output as a function of the first set of contextual information, wherein generating the diagnostic output comprises:
receiving a first training data set including a plurality of first data entries, each first data entry of the plurality of first data entries comprises examples of contextual information as inputs correlated to examples of physiological state data as outputs;
receiving a second training data set including a plurality of second data entries, each second data entry of the plurality of second data entries comprises examples of physiological state data as inputs correlated to examples of prognostic labels as outputs;
training a machine-learning model using the first training data set and the second training data set; and
generating the diagnostic output by determining at least a prognostic label associated with the diagnostic output as a function of the first set of contextual information using the trained machine-learning model; and
at least a plan generator module, operating on the at least a server, the at least a plan generator module configured to: generate a comprehensive instruction set comprising a treatment plan for a user associated with the diagnostic output which comprises: receiving at least an element of user data including at least a constitutional restriction; and filtering the diagnostic output using the at least an element of user data to generate the comprehensive instruction set.
The closet arts relates to Baldwin (US20190206522A1) in view of Velez et al. (US20190057774A1 hereinafter Velez). Baldwin discloses implementing a natural language request processing engine (NLRPE). The NRLPE performs natural language processing on a portion of unstructured text in an electronic data structure to generate textual characteristics of the portion of unstructured text. The NRLPE annotates at least one phrase in the portion of unstructured text at least by linking the at least one phrase to one or more concepts specified in at least one ontological data structure based on the textual characteristics of the portion of unstructured text. Velez discloses A disease-specific ontology crafted by a consensus of expert clinicians may be used to semantically characterize/provide semantic meaning to dynamically changing patient electronic medical record (EMR) data in critical care settings. Hierarchical, directed node-edge-node graphs (concept maps or Vmaps) developed with an end-user friendly graphical user interface and ontology editor, can be used to represent structured clinical reasoning and serve as the first step in disease-specific ontology building.
However, the prior art does not disclose at least a plan generator module, operating on the at least a server, the at least a plan generator module configured to: generate a comprehensive instruction set comprising a treatment plan for a user associated with the diagnostic output which comprises: receiving at least an element of user data including at least a constitutional restriction; and filtering the diagnostic output using the at least an element of user data to generate the comprehensive instruction set.
Claims 1-5, 8-15, 18-20 would be allowable if rewritten to overcome the
rejection(s) under Double Patent, as set forth in this Office action and to include all of
the limitations of the base claim and any intervening claims
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/HIEP V NGUYEN/Primary Examiner, Art Unit 3686