IP Library Granted Patent US 12,705,672
Granted Patent B1
US 12,705,672 · App. 16/659,438 · Granted Aug 11, 2026

Use determination risk coverage datastructure for on-demand and increased efficiency coverage detection and rebalancing apparatuses, methods and systems

Inventors: Anthony Miller (Minneapolis, MN); Henning Chiv (Castro Valley, CA); Matthew Chock (Eagan, MN); Glen Eiden (Forest Lake, MN); Trevor Fast (San Francisco, CA); Charley Hastings (Cape Coral, FL); Jason Haupt (Maple Grove, MN); Shawn Wagoner (Edina, MN); Matthew Wiandt (Bloomington, MN); David Dickey (Minneapolis, MN); Jessica Zeaske (Minneapolis, MN); Nels Marcus Thygeson (San Rafael, CA)
Assignee: Bind Benefits, Inc.
G06Q40/08G06Q10/067
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Quick Facts
Patent No.
US 12,705,672
App. No.
16/659,438
Granted
Aug 11, 2026
Kind
B1
Abstract

The Use Determination Risk Coverage Datastructure for On-Demand and Increased Efficiency Coverage Detection and Rebalancing Apparatuses, Methods and Systems (“UDRCD”) transforms coverage enrollment request, event signal, ACGG request, search request inputs via UDRCD components into coverage enrollment response, add-in recommendation, ACGG response, search response outputs. An add-in recommendation request associated with a plan member is obtained. A condition associated with the request is determined. A set of treatment paths associated with the condition is determined. A member state associated with the plan member is determined. The plan member's treatment path location is determined. A high value treatment path is determined from available treatment paths. An atomized add-in that provides coverage for the treatment path is determined. A set of providers for the atomized add-in is determined, and an expected longitudinal treatment value and copay are calculated for each provider. A best provider is determined. An atomized add-in recommendation is provided.

Claims (88)

1 . A system comprising:

one or more processors; and

at least one memory storing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving an add-in recommendation request associated with a plan data structure;

generating, based on clinical condition data, a use determination risk coverage graph topology data structure (UDRCD) comprising an atomized coverage graph depicting a set of one or more treatment paths, a set of one or more treatment objects associated with the set of one or more treatment paths, and a set of one or more provider objects associated with the set of one or more treatment paths, wherein:

(i) a first provider object of the set of one or more provider objects specifies a likelihood that a provider utilizes a treatment path of the set of one or more treatment paths,

(ii) the atomized coverage graph comprises a self-updating data structure configured to perform self-updating of the self-updating data structure based on updated treatment path data, and

(iii) the UDRCD comprises a multi-directional and self-referential data structure;

determining, based on event signal data associated with a plan member associated with the plan data structure, a condition associated with the add-in recommendation request;

determining, based on the set of one or more treatment objects and the set of one or more provider objects of the UDRCD, a second set of one or more treatment paths associated with the condition, wherein a first treatment path of the second set of one or more treatment paths comprises a first subset of treatment pathway nodes of the UDRCD;

identifying, based on clinical data associated with the plan member specific to the second set of one or more treatment paths, a plan member treatment path location;

selecting, based on a second subset of treatment pathway nodes of the UDRCD and the plan member treatment path location, an available treatment path of the set of one or more treatment paths of the set of one or more treatment paths comprising a key treatment pathway node corresponding to the plan member treatment path location;

determining, based on provider data, a set of one or more providers providing an atomized add-in that provides coverage for the available treatment path;

determining, based on evaluating a set of one or more expected longitudinal treatment values associated with the set of one or more providers, a selected provider from the set of one or more providers that is associated with a lowest expected longitudinal treatment value of the set of one or more expected longitudinal treatment values relative to other providers of the set of one or more providers;

generating, based on the available treatment path, the atomized add-in, and the selected provider, an atomized add-in recommendation for the plan member; and

generating, a user interface configured to provide (i) a display of the atomized add-in recommendation for the plan member and (ii) an interface component configured to receive data for supplementing the atomized add-in recommendation.

2 . The system of claim 1 , wherein the operations further comprise:

receiving an event signal corresponding to the plan member, wherein the event signal comprises one or more of: a coverage search by the plan member, a health care electronic data interchange transaction associated with the plan member, or an electronic health information message associated with the plan member; and

determining, further based on the event signal, the condition associated with the add-in recommendation request.

3 . The system of claim 1 , wherein the condition associated with the add-in recommendation request is determined further based on a coverage search query specified by the plan member.

4 . The system of claim 1 , wherein the atomized coverage graph is configured to perform self-updating further based on data for supplementing the atomized add-in recommendation as received via the interface component.

5 . The system of claim 1 , wherein to determine the set of one or more treatment paths associated with the condition, the operations further comprise:

determining a clinical condition object in the atomized coverage graph corresponding to the condition associated with the add-in recommendation request; and

determining a treatment paths object in the atomized coverage graph associated with the clinical condition object.

6 . The system of claim 1 , wherein the plan member treatment path location is determined further based on a treatment path move sequence associated with the plan member.

7 . The system of claim 1 , wherein the atomized add-in is a treatment add-in that provides coverage for a next treatment that the plan member must utilize to follow the available treatment path from the plan member treatment path location.

8 . The system of claim 1 , wherein the atomized add-in is a condition add-in that provides coverage for the condition.

9 . The system of claim 1 , wherein the operations further comprise:

determining a provider object in the atomized coverage graph corresponding to a respective provider of the set of one or more providers;

determining a propensity ranking based on practice patterns data associated with the provider object;

determining a propensity weight based on the plan member treatment path location;

determining an expected episodic cost for a next expected treatment for the condition based on treatment cost data associated with the provider object;

determining an episodic cost weight based on the plan member treatment path location; and

determining an expected longitudinal treatment value for the respective provider as a weighted average of the propensity ranking, weighted by the propensity weight, and the expected episodic cost weighted by the episodic cost weight.

10 . The system of claim 1 , wherein the operations further comprise:

determining a base copay for the atomized add-in based on an average longitudinal treatment value for the set of one or more providers;

determining, for a respective provider, a price factor indicative of a relative expense of an expected longitudinal treatment value for the respective provider as compared with the average longitudinal treatment value for other providers in the set of one or more providers; and

determining a copay for the atomized add-in for the respective provider as the base copay for the respective provider adjusted by the price factor for the respective provider.

11 . The system of claim 10 , wherein the set of one or more providers comprises one or more providers in a region associated with the plan member.

12 . The system of claim 1 , wherein a copay for the atomized add-in is adjusted based on a treatment path move sequence associated with the plan member.

13 . The system of claim 1 , wherein the operations further comprise:

generating, via an enrollment user interface, a notification with the atomized add-in recommendation for the plan member;

receiving, via the enrollment user interface, a selection of the atomized add-in from the plan member; and

providing, via the enrollment user interface, information regarding the set of one or more providers available for the atomized add-in, wherein the selected provider is highlighted for the plan member.

14 . The system of claim 13 , wherein the information regarding the set of one or more providers available for the atomized add-in comprises a map component that shows a location of each provider and a copay associated with each provider on a map.

15 . One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving an add-in recommendation request associated with a plan data structure;

generating, based on clinical condition data, a use determination risk coverage graph topology data structure (UDRCD) comprising an atomized coverage graph depicting a set of one or more treatment paths, a set of one or more treatment objects associated with the set of one or more treatment paths, and a set of one or more provider objects associated with the set of one or more treatment paths, wherein;

(i) a first provider object of the set of one or more provider objects specifies a likelihood that a provider utilizes a treatment path of the set of one or more treatment paths,

(ii) the atomized coverage graph is a self-updating data structure configured to perform self-updating of the self-updating data structure based on updated treatment path data, and

(iii) the UDRCD comprises a multi-directional and self-referential data structure;

determining, based on event signal data associated with a plan member associated with the plan data structure, a condition associated with the add-in recommendation request;

determining, based on the set of one or more treatment objects and the set of one or more provider objects of the UDRCD, a second set of one or more treatment paths associated with the condition wherein a first treatment path of the second set of one or more treatment paths comprises a first subset of one or more treatment pathway nodes of the UDRCD;

identifying, based on clinical data associated with the plan member specific to the second set of one or more treatment paths, a plan member treatment path location;

selecting, based on a second sub-set of treatment pathway nodes of the UDRCD and the plan member treatment path location, an available treatment path of the set of one or more treatment paths comprising a key treatment pathway node corresponding to the plan member treatment path location;

determining, based on provider data, a set of one or more providers providing an atomized add-in that provides coverage for the available treatment path;

determining, based on evaluating a set of one or more expected longitudinal treatment values associated with the set of one or more providers, a selected provider from the set of one or more providers that is associated with a lowest expected longitudinal treatment value of the set of one or more expected longitudinal treatment values relative to other providers of the set of one or more providers;

generating, based on the available treatment path, the atomized add-in, and the selected provider, an atomized add-in recommendation for the plan member; and

generating, a user interface configured to provide (i) a display of the atomized add-in recommendation for the plan member and (ii) an interface component configured to receive data for supplementing the atomized add-in recommendation.

16 . A processor-implemented add-in upgrade recommendation system, comprising:

an add-in recommendation determining component means, to:

receiving an add-in recommendation request associated with a plan data structure;

generating, based on clinical condition data, a use determination risk coverage graph topology data structure (UDRCD) comprising an atomized coverage graph depicting a set of one or more treatment paths, a set of one or more treatment objects associated with the set of one or more treatment paths, and a set of one or more provider objects associated with the set of one or more treatment paths, wherein:

(i) a first provider object of the set of one or more provider objects specifies a likelihood that a provider utilizes a treatment path of the set of one or more treatment paths,

(ii) the atomized coverage graph is a self-updating data structure configured to perform self-updating of the self-updating data structure based on updated treatment path data, and

(iii) the UDRCD comprises a multi-directional and self-referential data structure;

determining, based on event signal data associated with a plan member associated with the plan data structure, a condition associated with the add-in recommendation request;

determining, based on the set of one or more treatment objects and the set of one or more provider objects of the UDRCD, a second set of one or more treatment paths associated with the condition wherein a first treatment path of the second set of one or more treatment paths comprises a first subset of one or more treatment pathway nodes of the UDRCD;

identifying, based on clinical data associated with the plan member specific to the second set of one or more treatment paths, a plan member treatment path location;

selecting, based on a second sub-set of treatment pathway nodes of the UDRCD and the plan member treatment path location, an available treatment path of the set of one or more treatment paths comprising a key treatment pathway node corresponding to the plan member treatment path location;

determining, based on provider data, a set of one or more providers providing an atomized add-in that provides coverage for the available treatment path;

determining, based on evaluating a set of one or more expected longitudinal treatment values associated with the set of one or more providers, a selected provider from the set of one or more providers that is associated with a lowest expected longitudinal treatment value of the set of one or more expected longitudinal treatment values relative to other providers of the set of one or more providers;

generating, based on the available treatment path, the atomized add-in, and the selected provider, an atomized add-in recommendation for the plan member; and

generating, a user interface configured to provide (i) a display of the atomized add-in recommendation for the plan member and (ii) an interface component configured to receive data for supplementing the atomized add-in recommendation.

17 . A processor-implemented add-in upgrade recommendation method, comprising:

receiving, by one or more processors, an add-in recommendation request associated with a plan data structure;

generating, by the one or more processors and based on a set of clinical condition data, a use determination risk coverage graph topology data structure (UDRCD) comprising an atomized coverage graph depicting a set of one or more treatment paths, a set of one or more treatment objects associated with the set of one or more treatment paths, and a set of one or more provider objects associated with the set of one or more treatment paths, wherein;

(i) a first provider object of the set of one or more provider objects specifies a likelihood that a provider utilizes a treatment path of the set of one or more treatment paths,

(ii) the atomized coverage graph is a self-updating data structure configured to perform self-updating of the self-updating data structure based on updated treatment path data, and

(iii) the UDRCD comprises a multi-directional and self-referential data structure;

determining, by the one or more processors and based on event signal data associated with a plan member associated with the plan data structure, a condition associated with the add-in recommendation request;

determining, by the one or more processors and based on the set of one or more treatment objects and the set of one or more provider objects of the UDRCD, a second set of one or more treatment paths associated with the condition wherein a first treatment path of the second set of one or more treatment paths comprises a first subset of one or more treatment pathway nodes of the UDRCD;

identifying, by the one or more processors and based on clinical data associated with the plan member specific to the second set of one or more treatment paths, a plan member treatment path location;

selecting, by the one or more processors and based on a second subset of treatment pathway nodes of the UDRCD and the plan member treatment path location, an available treatment path of the set of one or more treatment paths comprising a key treatment pathway node corresponding to the plan member treatment path location;

determining, by the one or more processors and based on a set of provider data, a set of one or more providers providing an atomized add-in that provides coverage for the available treatment path;

determining, by the one or more processors and based on evaluating a set of one or more expected longitudinal treatment values associated with the set of one or more providers, a selected provider from the set of one or more providers that is associated with a lowest expected longitudinal treatment value of the set of one or more expected longitudinal treatment values relative to other providers of the set of one or more providers;

generating, by the one or more processors and based on the available treatment path, the atomized add-in, and the selected provider, an atomized add-in recommendation for the plan member; and

generating, by the one or more processors, a user interface configured to provide (i) a display of the atomized add-in recommendation for the plan member and (ii) an interface component configured to receive data for supplementing the atomized add-in recommendation.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2023
From: MILLER, ANTHONY; DICKEY, DAVID; CHIV, HENNING; CHOCK, MATTHEW; EIDEN, GLEN; FAST, TREVOR; WAGONER, SHAWN; WIANDT, MATTHEW; ZEASKE, JESSICA; THYGESON, NELS MARCUS; HAUPT, JASON; HASTINGS, CHARLEY
To: BIND BENEFITS, INC.
Reel/Frame 063486/0532 →
Continuity (7)
Continuation 15631961 · Jun 23, 2017
Continuation In Part 15632052 · Jun 23, 2017
Provisional Application 62807711 · Feb 19, 2019
Provisional Application 62748518 · Oct 21, 2018
Provisional Application 62524188 · Jun 23, 2017
Provisional Application 62510215 · May 23, 2017
Provisional Application 62446810 · Jan 16, 2017
References Cited (400)
US 5301105A · Cummings · 1994 [cited by applicant]
US 5523942A · Tyler · 1996 [cited by applicant]
US 5542078A · Martel et al. · 1996 [cited by applicant]
US 5855005A · Schuler et al. · 1998 [cited by applicant]
US 6061657A · Whiting-O'Keefe · 2000 [cited by applicant]
US 6078890A · Mangin et al. · 2000 [cited by applicant]
US 6151604A · Wlaschin · 2000 [cited by examiner]
US 6163775A · Wlaschin · 2000 [cited by examiner]
US 6266645B1 · Simpson · 2001 [cited by applicant]
US 6370511B1 · Dang · 2002 [cited by applicant]
US 6381576B1 · Gilbert · 2002 [cited by applicant]
US 6735569B1 · Wizig · 2004 [cited by applicant]
US 7392201B1 · Binns · 2008 [cited by applicant]
US 7493264B1 · Kelly · 2009 [cited by applicant]
US 7617115B2 · McNair · 2009 [cited by applicant]
US 7702522B1 · Sholem · 2010 [cited by applicant]
US 7702527B1 · Kron · 2010 [cited by applicant]
US 7711577B2 · Dust · 2010 [cited by applicant]
US 7805318B1 · Kuhn · 2010 [cited by applicant]
US 7979290B2 · Dang · 2011 [cited by applicant]
US 8005687B1 · Pederson · 2011 [cited by applicant]
US 8041636B1 · Hunter · 2011 [cited by applicant]
US 8050937B1 · Henderson · 2011 [cited by applicant]
US 8055519B1 · Trobiani · 2011 [cited by applicant]
US 8121869B2 · Dang · 2012 [cited by applicant]
US 8126727B2 · Peterson · 2012 [cited by applicant]
US 8321372B1 · Rakshit et al. · 2012 [cited by applicant]
US 8352286B1 · Bawa · 2013 [cited by applicant]
US 8388348B2 · Biltz et al. · 2013 [cited by applicant]
US 8401879B1 · Kazenas · 2013 [cited by applicant]
US 8407064B1 · Klieman et al. · 2013 [cited by applicant]
US 8412537B1 · Fenton · 2013 [cited by applicant]
US 8670996B1 · Weiss · 2014 [cited by applicant]
US 8805701B2 · Camacho et al. · 2014 [cited by applicant]
US 8868436B2 · Gotthardt · 2014 [cited by applicant]
US 9679028B1 · Sanghvi et al. · 2017 [cited by applicant]
US 9881129B1 · Cave · 2018 [cited by applicant]
US 10049772B1 · Price et al. · 2018 [cited by applicant]
US 10460411B2 · Liu · 2019 [cited by applicant]
US 10521864B1 · Davis · 2019 [cited by applicant]
US 10678821B2 · Carmeli et al. · 2020 [cited by applicant]
US 11107582B2 · Nicolaas · 2021 [cited by examiner]
US 11244416B2 · Cave et al. · 2022 [cited by applicant]
US 11270800B1 · Mitidis et al. · 2022 [cited by applicant]
US 11373739B2 · Ozeran · 2022 [cited by examiner]
US 11386999B2 · Basu · 2022 [cited by applicant]
US 11508006B1 · Cross et al. · 2022 [cited by applicant]
US 11539506B2 · Lee et al. · 2022 [cited by applicant]
US 11640857B2 · Valuck et al. · 2023 [cited by applicant]
US 11663670B1 · Miller et al. · 2023 [cited by applicant]
US 11705226B2 · Colley · 2023 [cited by examiner]
US 11790454B1 · Miller et al. · 2023 [cited by applicant]
US 11967431B1 · Toensing et al. · 2024 [cited by applicant]
US 12020816B2 · Srinivasan et al. · 2024 [cited by applicant]
US 12094582B1 · Goyal et al. · 2024 [cited by applicant]
US 12131397B2 · Cave et al. · 2024 [cited by applicant]
US 12211598B1 · Aravamudan et al. · 2025 [cited by applicant]
US 12259864B1 · Aravamudan et al. · 2025 [cited by applicant]
US 20010034619A1 · Sherman · 2001 [cited by applicant]
US 20020065758A1 · Henley · 2002 [cited by examiner]
US 20020087358A1 · Gilbert · 2002 [cited by applicant]
US 20020111826A1 · Potter et al. · 2002 [cited by applicant]
US 20020165738A1 · Dang · 2002 [cited by applicant]
US 20020173987A1 · Dang · 2002 [cited by applicant]
US 20020173989A1 · Dang · 2002 [cited by applicant]
US 20020173992A1 · Dang · 2002 [cited by applicant]
US 20020178030A1 · Loeb · 2002 [cited by examiner]
US 20030195838A1 · Henley · 2003 [cited by examiner]
US 20030204421A1 · Houle · 2003 [cited by applicant]
US 20040010426A1 · Berdou · 2004 [cited by applicant]
US 20040111363A1 · Trench · 2004 [cited by examiner]
US 20040122704A1 · Sabol et al. · 2004 [cited by applicant]
US 20040122787A1 · Avinash et al. · 2004 [cited by applicant]
US 20040143464A1 · Houle · 2004 [cited by applicant]
US 20040193456A1 · Kellington · 2004 [cited by applicant]
US 20050010446A1 · Lash et al. · 2005 [cited by applicant]
US 20050020903A1 · Krishnan et al. · 2005 [cited by applicant]
US 20050049497A1 · Krishnan et al. · 2005 [cited by applicant]
US 20050055251A1 · Ashley · 2005 [cited by applicant]
US 20050060195A1 · Bessette et al. · 2005 [cited by applicant]
US 20050137932A1 · D'Angelo et al. · 2005 [cited by applicant]
US 20050182659A1 · Huttin · 2005 [cited by examiner]
US 20050203830A1 · Prieston · 2005 [cited by applicant]
US 20050256745A1 · Dalton · 2005 [cited by applicant]
US 20060089862A1 · Anandarao · 2006 [cited by applicant]
US 20060200407A1 · Hartley · 2006 [cited by applicant]
US 20070021986A1 · Cheung · 2007 [cited by applicant]
US 20070021988A1 · Dang · 2007 [cited by applicant]
US 20070118399A1 · Avinash et al. · 2007 [cited by applicant]
US 20070156455A1 · Tarino · 2007 [cited by applicant]
US 20070162308A1 · Peters · 2007 [cited by applicant]
US 20070179871A1 · Minor et al. · 2007 [cited by applicant]
US 20070238065A1 · Sherwood et al. · 2007 [cited by applicant]
US 20070271119A1 · Boeger · 2007 [cited by applicant]
US 20070276704A1 · Naumann · 2007 [cited by applicant]
US 20080010097A1 · Williams et al. · 2008 [cited by applicant]
US 20080033756A1 · Peterson · 2008 [cited by applicant]
US 20080103991A1 · Moore et al. · 2008 [cited by applicant]
US 20080109263A1 · Clark · 2008 [cited by applicant]
US 20080120143A1 · Beauregard · 2008 [cited by applicant]
US 20080147441A1 · Kil · 2008 [cited by applicant]
US 20080154648A1 · Babyak et al. · 2008 [cited by applicant]
US 20080154759A1 · Babyak et al. · 2008 [cited by applicant]
US 20080183504A1 · Highley · 2008 [cited by applicant]
US 20080201172A1 · McNamar · 2008 [cited by applicant]
US 20080208640A1 · Thomas · 2008 [cited by applicant]
US 20080243547A1 · Brett · 2008 [cited by examiner]
US 20080275737A1 · Gentry · 2008 [cited by examiner]
US 20080288286A1 · Noreen · 2008 [cited by applicant]
US 20080306952A1 · Lynn et al. · 2008 [cited by applicant]
US 20090076841A1 · Baker · 2009 [cited by applicant]
US 20090112632A1 · Belliveau · 2009 [cited by applicant]
US 20090125348A1 · Rastogi · 2009 [cited by applicant]
US 20090248481A1 · Dick et al. · 2009 [cited by applicant]
US 20090276249A1 · Dust et al. · 2009 [cited by applicant]
US 20100030579A1 · Dhauvan · 2010 [cited by applicant]
US 20100088112A1 · Krasny · 2010 [cited by applicant]
US 20100131284A1 · Duffy · 2010 [cited by examiner]
US 20100223072A1 · Jacobson · 2010 [cited by applicant]
US 20100235197A1 · Dang · 2010 [cited by applicant]
US 20100235295A1 · Zides · 2010 [cited by examiner]
US 20100241449A1 · Firminger · 2010 [cited by applicant]
US 20100268057A1 · Firminger et al. · 2010 [cited by applicant]
US 20100268108A1 · Firminger · 2010 [cited by applicant]
US 20100274577A1 · Firminger · 2010 [cited by applicant]
US 20100274578A1 · Firminger · 2010 [cited by applicant]
US 20100293002A1 · Firminger · 2010 [cited by applicant]
US 20100305962A1 · Firminger · 2010 [cited by applicant]
US 20110010190A1 · Falchuk et al. · 2011 [cited by applicant]
US 20110028885A1 · Eggers et al. · 2011 [cited by applicant]
US 20110035231A1 · Firminger · 2011 [cited by applicant]
US 20110046985A1 · Raheman · 2011 [cited by examiner]
US 20110082712A1 · Eberhardt et al. · 2011 [cited by applicant]
US 20110125520A1 · Dhoble · 2011 [cited by applicant]
US 20110153369A1 · Feldman · 2011 [cited by applicant]
US 20110161117A1 · Busque · 2011 [cited by applicant]
US 20110161118A1 · Borden · 2011 [cited by applicant]
US 20110166895A1 · Kron · 2011 [cited by applicant]
US 20110202370A1 · Green et al. · 2011 [cited by applicant]
US 20110225114A1 · Gotthardt · 2011 [cited by applicant]
US 20110282690A1 · Patel · 2011 [cited by examiner]
US 20110288879A1 · Gice et al. · 2011 [cited by applicant]
US 20110301977A1 · Belcher · 2011 [cited by examiner]
US 20110301982A1 · Green et al. · 2011 [cited by applicant]
US 20120010898A1 · Dust et al. · 2012 [cited by applicant]
US 20120010900A1 · Kaniadakis · 2012 [cited by applicant]
US 20120016692A1 · Jenkins-Robbins · 2012 [cited by applicant]
US 20120022984A1 · Morrison · 2012 [cited by applicant]
US 20120035975A1 · Sugimoto · 2012 [cited by applicant]
US 20120047105A1 · Saigal · 2012 [cited by applicant]
US 20120066662A1 · Chao · 2012 [cited by applicant]
US 20120129139A1 · Partovi · 2012 [cited by applicant]
US 20120239560A1 · Pourfallah · 2012 [cited by applicant]
US 20120259654A1 · Vanderzee · 2012 [cited by applicant]
US 20120284058A1 · Varanasi · 2012 [cited by applicant]
US 20120310679A1 · Olson · 2012 [cited by applicant]
US 20120330690A1 · Goslinga · 2012 [cited by applicant]
US 20130006672A1 · Dang · 2013 [cited by applicant]
US 20130007761A1 · O'Sullivan et al. · 2013 [cited by applicant]
US 20130030828A1 · Pourfallah et al. · 2013 [cited by applicant]
US 20130035956A1 · Carmeli · 2013 [cited by applicant]
US 20130090948A1 · Upadhyayula et al. · 2013 [cited by applicant]
US 20130124217A1 · Thesman · 2013 [cited by applicant]
US 20130166317A1 · Beardall · 2013 [cited by examiner]
US 20130185231A1 · Baras · 2013 [cited by applicant]
US 20130191135A1 · Camacho et al. · 2013 [cited by applicant]
US 20130191157A1 · Eiden · 2013 [cited by applicant]
US 20130191159A1 · Camacho et al. · 2013 [cited by applicant]
US 20130246086A1 · Mun et al. · 2013 [cited by applicant]
US 20130304506A1 · Gallivan et al. · 2013 [cited by applicant]
US 20140006066A1 · Watts · 2014 [cited by applicant]
US 20140052470A1 · Ashford · 2014 [cited by applicant]
US 20140058738A1 · Yeskel · 2014 [cited by applicant]
US 20140074518A1 · Ilgenfritz · 2014 [cited by applicant]
US 20140081667A1 · Joao · 2014 [cited by applicant]
US 20140114674A1 · Krughoff · 2014 [cited by examiner]
US 20140136241A1 · Rakshit et al. · 2014 [cited by applicant]
US 20140142861A1 · Hagstrom et al. · 2014 [cited by applicant]
US 20140142964A1 · Lang · 2014 [cited by applicant]
US 20140172470A1 · Watts · 2014 [cited by applicant]
US 20140180714A1 · Mun · 2014 [cited by applicant]
US 20140180949A1 · Ramasamy · 2014 [cited by applicant]
US 20140249851A1 · Christodouleas · 2014 [cited by examiner]
US 20140257852A1 · Walker et al. · 2014 [cited by applicant]
US 20140288958A1 · Hummer et al. · 2014 [cited by applicant]
US 20140297297A1 · Head · 2014 [cited by applicant]
US 20140304009A1 · Saxon · 2014 [cited by applicant]
US 20140372150A1 · Karle · 2014 [cited by applicant]
US 20150006192A1 · Sudharsan · 2015 [cited by examiner]
US 20150006206A1 · Mdeway · 2015 [cited by examiner]
US 20150073943A1 · Norris · 2015 [cited by applicant]
US 20150088541A1 · Yao · 2015 [cited by examiner]
US 20150112728A1 · Baym et al. · 2015 [cited by applicant]
US 20150112729A1 · Baym et al. · 2015 [cited by applicant]
US 20150161622A1 · Hoffmann · 2015 [cited by applicant]
US 20150199493A1 · Glenn · 2015 [cited by applicant]
US 20150254754A1 · Lang et al. · 2015 [cited by applicant]
US 20150339602A1 · Schlosser · 2015 [cited by applicant]
US 20150356685A1 · Lindbberg · 2015 [cited by applicant]
US 20160042135A1 · Hogan · 2016 [cited by examiner]
US 20160071432A1 · Kurowski et al. · 2016 [cited by applicant]
US 20160092641A1 · Delaney · 2016 [cited by applicant]
US 20160125362A1 · Dziuba · 2016 [cited by applicant]
US 20160140295A1 · Powell · 2016 [cited by examiner]
US 20160196398A1 · Vivero · 2016 [cited by examiner]
US 20160246941A1 · Miller · 2016 [cited by examiner]
US 20160292367A1 · Thorpe · 2016 [cited by examiner]
US 20160292371A1 · Alhimiri · 2016 [cited by examiner]
US 20160321316A1 · Pennefather et al. · 2016 [cited by applicant]
US 20160321412A1 · Basri · 2016 [cited by applicant]
US 20160350495A1 · Pecora · 2016 [cited by applicant]
US 20160358295A1 · Heffley · 2016 [cited by applicant]
US 20160371447A1 · Koman · 2016 [cited by applicant]
US 20160378932A1 · Sperling · 2016 [cited by applicant]
US 20170031870A1 · Grealish et al. · 2017 [cited by applicant]
US 20170070523A1 · Bailey et al. · 2017 [cited by applicant]
US 20170140393A1 · Katz-Rogozhnikov · 2017 [cited by applicant]
US 20170168070A1 · Oberoi et al. · 2017 [cited by applicant]
US 20170169173A1 · Snow et al. · 2017 [cited by applicant]
US 20170193173A1 · Miller · 2017 [cited by applicant]
US 20170235900A1 · Messina · 2017 [cited by applicant]
US 20170262604A1 · Francois · 2017 [cited by examiner]
US 20170339184A1 · Bailey et al. · 2017 [cited by applicant]
US 20180047120A1 · Mathis · 2018 [cited by applicant]
US 20180121614A1 · Connely et al. · 2018 [cited by applicant]
US 20180121843A1 · Connely et al. · 2018 [cited by applicant]
US 20180157799A1 · Ketterer · 2018 [cited by examiner]
US 20180166157A1 · Firminger · 2018 [cited by applicant]
US 20180182475A1 · Cossler et al. · 2018 [cited by applicant]
US 20180197636A1 · Firminger · 2018 [cited by applicant]
US 20180218456A1 · Kolb et al. · 2018 [cited by applicant]
US 20180260905A1 · Andreae · 2018 [cited by applicant]
US 20180301222A1 · Dew · 2018 [cited by applicant]
US 20190102670A1 · Ceulemans et al. · 2019 [cited by applicant]
US 20190164118A1 · Sandberg et al. · 2019 [cited by applicant]
US 20200077892A1 · Tran · 2020 [cited by examiner]
US 20200118691A1 · Kiljanek · 2020 [cited by applicant]
US 20200185074A1 · Czerska · 2020 [cited by examiner]
US 20200185100A1 · Francois · 2020 [cited by examiner]
US 20200251204A1 · Teodoro et al. · 2020 [cited by applicant]
US 20200303069A1 · Mulligan et al. · 2020 [cited by applicant]
US 20200335188A1 · Ozeran · 2020 [cited by examiner]
US 20210020280A1 · Hutchison et al. · 2021 [cited by applicant]
US 20210043310A1 · Valuck · 2021 [cited by applicant]
US 20210056639A1 · Eberting · 2021 [cited by applicant]
US 20210090694A1 · Colley · 2021 [cited by applicant]
US 20210118577A1 · Bettencourt-Silva et al. · 2021 [cited by applicant]
US 20210135841A1 · Lee et al. · 2021 [cited by applicant]
US 20210174963A1 · Hill · 2021 [cited by applicant]
US 20210201417A1 · Neumann · 2021 [cited by examiner]
US 20210241907A1 · Basu · 2021 [cited by applicant]
US 20210304881A1 · White et al. · 2021 [cited by applicant]
US 20210313049A1 · Khan et al. · 2021 [cited by applicant]
US 20210374874A1 · Basu et al. · 2021 [cited by applicant]
US 20210407672A1 · Zumbrun · 2021 [cited by applicant]
US 20210407682A1 · Crossen · 2021 [cited by applicant]
US 20220172841A1 · Steinberg-Koch et al. · 2022 [cited by applicant]
US 20220254466A1 · Hwang · 2022 [cited by examiner]
US 20220277840A1 · Lester et al. · 2022 [cited by applicant]
US 20220319652A1 · Ozeran · 2022 [cited by examiner]
US 20220359080A1 · Basu · 2022 [cited by applicant]
US 20230005072A1 · Sanchez · 2023 [cited by applicant]
US 20230103143A1 · Srinivasan et al. · 2023 [cited by applicant]
US 20230133829A1 · Kumar et al. · 2023 [cited by applicant]
US 20230138488A1 · Lee et al. · 2023 [cited by applicant]
US 20230196471A1 · Mendell et al. · 2023 [cited by applicant]
US 20230268070A1 · Nienstedt et al. · 2023 [cited by applicant]
US 20230274809A1 · Dimitrova · 2023 [cited by examiner]
US 20230352134A1 · Hasan et al. · 2023 [cited by applicant]
US 20230395214A1 · Needs et al. · 2023 [cited by applicant]
US 20240047052A1 · Ruiz et al. · 2024 [cited by applicant]
US 20240144091A1 · Adjaoute · 2024 [cited by applicant]
US 20240242802A1 · Yazdavar et al. · 2024 [cited by applicant]
US 20240281832A1 · Trauman et al. · 2024 [cited by applicant]
US 20240403967A1 · Chehrazi et al. · 2024 [cited by applicant]
US 20250272149A1 · Eleti · 2025 [cited by examiner]
AU 2010306593A1 · 2012 [cited by applicant]
CA 2419105C · 2007 [cited by applicant]
CA 2369425C · 2012 [cited by applicant]
CA 3034235A1 · 2018 [cited by applicant]
CA 3076349A1 · 2018 [cited by applicant]
CA 2997585C · 2021 [cited by applicant]
CN 1748217A · 2006 [cited by applicant]
CN 1748218A · 2006 [cited by applicant]
CN 1914617A · 2007 [cited by applicant]
CN 104857422B · 2018 [cited by applicant]
CN 110675956A · 2020 [cited by applicant]
CN 115482921A · 2022 [cited by applicant]
CN 109376381B · 2024 [cited by applicant]
WO 9701141A1 · 1997 [cited by applicant]
WO 0060431A1 · 2000 [cited by applicant]
WO 0133484A2 · 2001 [cited by applicant]
WO 2011123823 · 2011 [cited by applicant]
WO WO2011123823A1 · 2011 [cited by examiner]
WO 2013052733A1 · 2013 [cited by applicant]
WO 2013109973A1 · 2013 [cited by applicant]
WO 2014130392 · 2014 [cited by applicant]
WO WO2014130392A1 · 2014 [cited by examiner]
WO 2015054794A1 · 2015 [cited by applicant]
WO 2015191562 · 2015 [cited by applicant]
WO WO2015191562A1 · 2015 [cited by examiner]
WO 2018034913A1 · 2018 [cited by applicant]
WO 2018057918A1 · 2018 [cited by applicant]
D. C. Stahl, L. Rouse, D. Ko and J. C. Niland, “GDSI: a Web-based decision support system to facilitate the efficient and effective use of clinical practice guidelines,” Proc. of 37th Annual Hawaii Int'l Conf. on System… [cited by examiner]
V. Tresp, J. Marc Overhage, M. Bundschus, S. Rabizadeh, P. A. Fasching and S. Yu, “Going Digital: A Survey on Digitalization and Large-Scale Data Analytics in Healthcare,” in Proc. of the IEEE, vol. 104, No. 11, pp. 218… [cited by examiner]
Ongenae, Femke et al. “Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines.” BMC medical informatics and decision making vol. 10 3… [cited by examiner]
Karen Davis, Marilyn Moon, Barbara Cooper and Cathy Schoen. “Medicare Extra: A Comprehensive Benefit Option for Medicare Beneficiaries”. Health Affairs, (2005). doi: 10.1377/hlthaff.w5.442. http://content.healthaffairs.… [cited by applicant]
Peter Diamond. “Organizing the Health Insurance Market”. Econometrica, vol. 60, No. 6. (Nov., 1992), pp. 1233-1254. http:// links.jstor.org/sici?sici=0012-9682%28199211%2960%3A6%3C1233%3AOTHIM%3E2.0.CO%3B2-5 (Year: 1992… [cited by applicant]
Adam Atherly. “The Effect of Medicare Supplemental Insurance on Medicare Expenditures”. International Journal of Health Care Finance and Economics, 2, 137-162, 2002. (Year: 2002). [cited by applicant]
Mark V. Pauly, Patricia Danzon, Paul Feldstein, and John Hoff. “A Plan for ‘Responsible National Health Insurance’”. Health Affairs, pp. 5-25, Spring (1991). (Year: 1991). [cited by applicant]
Susan L. Ettner. “Adverse selection and the purchase of Medigap insurance by the elderly”. Journal of Health Economics. vol. 16, Issue 5, Oct. 1997, pp. 543-562. https://doi.org/10.1016/S0167-6296(97)00011-8 (Year: 1997… [cited by applicant]
John H. Goddeeris and Andrew J. Hogan. “Improving Access to Health Care: What Can the States Do?” W.E. Upjohn Institute for Employment Research. (1992). ISBN 0-88099-117-8. (Year: 1992). [cited by applicant]
Dictionary.com. Definition of “Condition”. Collins English Dictionary—Complete & Unabridged 2012 Digital Edition. Downloaded on Aug. 3, 2019. https://www.dictionary.com/browse/condition (Year: 2012). [cited by applicant]
Dictionary.com. Definition of “Atomize”. Collins English Dictionary—Complete & Unabridged 2012 Digital Edition. Downloaded on Aug. 3, 2019. https://www.dictionary.com/browse/atomize (Year: 2012). [cited by applicant]
Geamsakul etal. “Analysis of Hepatitis Dataset by Decision Tree Based on Graph-Based Induction”. Annual Conference of the Japanese Society for Artificial Intelligence. JSAI 2004: New Frontiers in Artificial Intelligence… [cited by applicant]
Geamsakul et al. “Constructing a Decision Tree for Graph-Structured Data and its Applications”. Fundamenta Informaticae 66 (2005) 131-160 131. IOS Press. https://www.researchgate.net/publication/234785949_Constructing a… [cited by applicant]
Ling et al. “Decision trees with minimal costs”. ICML '04: Proceedings of the twenty-first international conference on Machine learning. Jul. 2004 https://doi.org/10.1145/1015330.1015369 (Year: 2004). [cited by applicant]
Desarkaret al. “Med-Tree: A User Knowledge Graph Framework for Medical Applications”. 13th IEEE International Conference on Bioinformatics and BioEngineering. Nov. 10-13, 2013. DOI: 10.1109/BIBE.2013.6701564 (Year: 2013… [cited by applicant]
U.S. Appl. No. 15/631,961 [cited by applicant]
U.S. Appl. No. 15/632,052 [cited by applicant]
U.S. Appl. No. 16/659,429 [cited by applicant]
U.S. Appl. No. 16/659,438 [cited by applicant]
U.S. Appl. No. 16/659,444 [cited by applicant]
U.S. Appl. No. 17/862,333 [cited by applicant]
U.S. Appl. No. 17/862,351 [cited by applicant]
U.S. Appl. No. 17/862,368 [cited by applicant]
U.S. Appl. No. 17/862,385 [cited by applicant]
U.S. Appl. No. 17/862,392 [cited by applicant]
U.S. Appl. No. 62/446,810 [cited by applicant]
U.S. Appl. No. 62/510,215 [cited by applicant]
U.S. Appl. No. 62/524,188 [cited by applicant]
U.S. Appl. No. 62/748,518 [cited by applicant]
U.S. Appl. No. 62/807,711 [cited by applicant]
U.S. Appl. No. 63/220,986 [cited by applicant]
U.S. Appl. No. 63/220,988 [cited by applicant]
U.S. Appl. No. 63/220,991 [cited by applicant]
U.S. Appl. No. 63/220,992 [cited by applicant]
U.S. Appl. No. 63/220,993 [cited by applicant]
Final Rejection Mailed on Dec. 26, 2023 for U.S. Appl. No. 17/862,333, 22 page(s). [cited by applicant]
Final Rejection Mailed on Sep. 9, 2024 for U.S. Appl. No. 17/862,385, 11 page(s). [cited by applicant]
Final Rejection Mailed on Sep. 10, 2024 for U.S. Appl. No. 17/862,368, 10 page(s). [cited by applicant]
Google Patents English language translation of CN-115482921-A. https://patents.google.com/patent/CN115482921A/en?oq=CN+115482921+A (Year: 2024). [cited by applicant]
Non-Final Rejection Mailed on May 8, 2023 for U.S. Appl. No. 17/862,333, 19 page(s). [cited by applicant]
Final Rejection Mailed on Oct. 21, 2024 for U.S. Appl. No. 16/659,444, 24 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Dec. 5, 2024 for U.S. Appl. No. 17/862,333, 2 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Nov. 22, 2024 for U.S. Appl. No. 17/862,333, 12 page(s). [cited by applicant]
Dewilde et al. “Modified Rankin scale as a determinant of direct medical costs after stroke”. International Journal of Stroke, 2017, vol. 12(4) 392-400. DOI: 10.1177/1747493017691984 journals.sagepub.com/home/wso (Year:… [cited by applicant]
Final Rejection Mailed on Apr. 5, 2023 for U.S. Appl. No. 15/632,052, 22 page(s). [cited by applicant]
Final Rejection Mailed on Apr. 10, 2020 for U.S. Appl. No. 15/632,052, 19 page(s). [cited by applicant]
Final Rejection Mailed on Aug. 20, 2024 for U.S. Appl. No. 15/632,052, 24 page(s). [cited by applicant]
Final Rejection Mailed on Aug. 22, 2024 for U.S. Appl. No. 17/862,392, 10 page(s). [cited by applicant]
Final Rejection Mailed on Feb. 1, 2021 for U.S. Appl. No. 16/659,444, 27 page(s). [cited by applicant]
Final Rejection Mailed on Jan. 4, 2022 for U.S. Appl. No. 15/631,961, 12 page(s). [cited by applicant]
Final Rejection Mailed on May 20, 2020 for U.S. Appl. No. 15/631,961, 21 page(s). [cited by applicant]
Final Rejection Mailed on Nov. 17, 2021 for U.S. Appl. No. 15/632,052, 22 page(s). [cited by applicant]
Final Rejection Mailed on Oct. 19, 2022 for U.S. Appl. No. 16/659,444, 26 page(s). [cited by applicant]
Google Patents English Language Translation of CN 104857422 B. https://patents.google.com/patent/CN104857422B/en?oq=CN+104857422+B (Year: 2024). [cited by applicant]
Google Patents English Language Translation of CN 110675956 A. https://patents.google.com/patent/CN110675956A/en?oq=CN+110675956+A (Year: 2024). [cited by applicant]
Google Patents English language translation of CN-1748217-A. https://patents.google.com/patent/CN1748217A/en?oq=CN-1748217-A (Year: 2024). [cited by applicant]
Google Patents English language translation of CN-1748218-A. https://patents.google.com/patent/CN1748218A/en?oq=CN-1748218-A (Year: 2024). [cited by applicant]
Google Patents English language translation of CN-1914617-A. https://patents.google.com/patent/CN1914617A/en?oq=CN-1914617-A (Year: 2024). [cited by applicant]
Hazen et al. “Stochastic-Tree Models in Medical Decision Making”. Interfaces 28: Jul. 4-Aug. 1998 (pp. 64-80). https://www.researchgate.net/publication/228391060_Stochastic-Tree_Models_in_Medical_Decision_Making (Year: … [cited by applicant]
Mar et al. “Outcomes measured by mortality rates, quality of life and degree of autonomy in the first year in stroke units in Spain”. Health and Quality of Life Outcomes (2015) 13:36 DOI 10.1186/s 12955-015-0230-8 (Year… [cited by applicant]
Non-Final Rejection Mailed on Aug. 2, 2021 for U.S. Appl. No. 16/659,429, 21 page(s). [cited by applicant]
Non-Final Rejection Mailed on Aug. 7, 2019 for U.S. Appl. No. 15/632,052, 24 page(s). [cited by applicant]
Non-Final Rejection Mailed on Aug. 22, 2022 for U.S. Appl. No. 15/632,052, 20 page(s). [cited by applicant]
Non-Final Rejection Mailed on Aug. 27, 2024 for U.S. Appl. No. 17/862,351, 18 page(s). [cited by applicant]
Non-Final Rejection Mailed on Feb. 10, 2021 for U.S. Appl. No. 15/632,052, 20 page(s). [cited by applicant]
Non-Final Rejection Mailed on Feb. 29, 2024 for U.S. Appl. No. 17/862,368, 11 page(s). [cited by applicant]
Non-Final Rejection Mailed on Feb. 29, 2024 for U.S. Appl. No. 17/862,385, 10 page(s). [cited by applicant]
Non-Final Rejection Mailed on Jan. 16, 2024 for U.S. Appl. No. 16/659,444, 29 page(s). [cited by applicant]
Non-Final Rejection Mailed on Jun. 2, 2020 for U.S. Appl. No. 16/659,444, 24 page(s). [cited by applicant]
Non-Final Rejection Mailed on Jun. 8, 2023 for U.S. Appl. No. 16/659,444, 29 page(s). [cited by applicant]
Non-Final Rejection Mailed on Mar. 3, 2022 for U.S. Appl. No. 16/659,444, 27 page(s). [cited by applicant]
Non-Final Rejection Mailed on Mar. 18, 2021 for U.S. Appl. No. 15/631,961, 27 page(s). [cited by applicant]
Non-Final Rejection Mailed on Nov. 2, 2023 for U.S. Appl. No. 15/632,052, 23 page(s). [cited by applicant]
Non-Final Rejection Mailed on Nov. 8, 2023 for U.S. Appl. No. 17/862,351, 17 page(s). [cited by applicant]
Non-Final Rejection Mailed on Oct. 6, 2023 for U.S. Appl. No. 17/862,392, 15 page(s). [cited by applicant]
Non-Final Rejection Mailed on Sep. 3, 2019 for U.S. Appl. No. 15/631,961, 19 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Dec. 2, 2022 for U.S. Appl. No. 15/631,961, 9 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Feb. 1, 2023 for U.S. Appl. No. 16/659,429, 14 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Jun. 7, 2022 for U.S. Appl. No. 16/659,429, 14 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Jun. 23, 2022 for U.S. Appl. No. 16/659,429, 10 page(s). [cited by applicant]
Szolovits. “Uncertainty and Decisions in Medical Informatics”. Article in Methods of Information in Medicine. Jan. 2001. DOI: 10.1055/S-0038-1634594 https://www.researchgate.net/publication/2453682 (Year: 2001). [cited by applicant]
Advisory Action (PTOL-303) Mailed on Jan. 8, 2025 for U.S. Appl. No. 16/659,444, 2 page(s). [cited by applicant]
Advisory Action (PTOL-303) Mailed on Mar. 20, 2025 for U.S. Appl. No. 17/862,351, 3 page(s). [cited by applicant]
Final Rejection Mailed on Jan. 15, 2025 for U.S. Appl. No. 17/862,351, 11 page(s). [cited by applicant]
Non-Final Rejection Mailed on Mar. 18, 2025 for U.S. Appl. No. 15/632,052, 12 page(s). [cited by applicant]
Non-Final Rejection Mailed on Mar. 21, 2025 for U.S. Appl. No. 17/862,368, 12 page(s). [cited by applicant]
Non-Final Rejection Mailed on Mar. 21, 2025 for U.S. Appl. No. 17/862,385, 12 page(s). [cited by applicant]
Google Patents English Language Translation of CN 109376381 B. (Year: 2025). [cited by applicant]
Non-Final Rejection Mailed on Apr. 29, 2025 for U.S. Appl. No. 16/659,444, 14 page(s). [cited by applicant]
Non-Final Rejection Mailed on May 15, 2025 for U.S. Appl. No. 17/862,351, 12 page(s). [cited by applicant]
Advisory Action (PTOL-303) Mailed on Oct. 27, 2025 for U.S. Appl. No. 15/632,052, 2 page(s). [cited by applicant]
Final Rejection Mailed on Aug. 21, 2025 for U.S. Appl. No. 15/632,052, 13 page(s). [cited by applicant]
Final Rejection Mailed on Aug. 22, 2025 for U.S. Appl. No. 17/862,368, 11 page(s). [cited by applicant]
Final Rejection Mailed on Aug. 26, 2025 for U.S. Appl. No. 17/862,385, 12 page(s). [cited by applicant]
Final Rejection Mailed on Oct. 28, 2025 for U.S. Appl. No. 16/659,444, 14 page(s). [cited by applicant]
Advisory Action (PTOL-303) Mailed on Feb. 2, 2026 for U.S. Appl. No. 17/862,351, 2 page(s). [cited by applicant]
Final Rejection Mailed on Nov. 28, 2025 for U.S. Appl. No. 17/862,351, 14 page(s). [cited by applicant]