WO2024077103A3 - Machine learning to predict therapy progression - Google Patents

Machine learning to predict therapy progression Download PDF

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Publication number
WO2024077103A3
WO2024077103A3 PCT/US2023/076010 US2023076010W WO2024077103A3 WO 2024077103 A3 WO2024077103 A3 WO 2024077103A3 US 2023076010 W US2023076010 W US 2023076010W WO 2024077103 A3 WO2024077103 A3 WO 2024077103A3
Authority
WO
WIPO (PCT)
Prior art keywords
machine learning
therapy
user
progress
predicted
Prior art date
Application number
PCT/US2023/076010
Other languages
French (fr)
Other versions
WO2024077103A2 (en
Inventor
Zhuo Qi LEE
Yang YAN
Yuan YONGSHAN
Alena MELNIKOVA
Tan Yu JIA
Original Assignee
Resmed Digital Health Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Resmed Digital Health Inc. filed Critical Resmed Digital Health Inc.
Publication of WO2024077103A2 publication Critical patent/WO2024077103A2/en
Publication of WO2024077103A3 publication Critical patent/WO2024077103A3/en

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Biomedical Technology (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Surgery (AREA)
  • Urology & Nephrology (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

Techniques for progress prediction using machine learning are provided. User data describing a user associated with a therapy plan is received, and a set of features is generated by applying one or more preprocessing transformations to the user data. A predicted therapy progress is generated for the user by processing the set of features using a trained machine learning model, where the predicted therapy progress comprises a stage, of a defined set of stages, associated with the therapy plan. Enrollment of the user in the therapy plan is facilitated based on the predicted therapy progress.
PCT/US2023/076010 2022-10-04 2023-10-04 Machine learning to predict therapy progression WO2024077103A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202263413142P 2022-10-04 2022-10-04
US63/413,142 2022-10-04

Publications (2)

Publication Number Publication Date
WO2024077103A2 WO2024077103A2 (en) 2024-04-11
WO2024077103A3 true WO2024077103A3 (en) 2024-05-10

Family

ID=90608826

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2023/076010 WO2024077103A2 (en) 2022-10-04 2023-10-04 Machine learning to predict therapy progression

Country Status (1)

Country Link
WO (1) WO2024077103A2 (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170209657A1 (en) * 2014-08-01 2017-07-27 Resmed Limited Self-optimising respiratory therapy system
US20170329933A1 (en) * 2016-05-13 2017-11-16 Thomas Edwin Brust Adaptive therapy and health monitoring using personal electronic devices
US20200005929A1 (en) * 2017-03-01 2020-01-02 Ieso Digital Health Limited Psychotherapy Triage Method
US20200320436A1 (en) * 2019-04-08 2020-10-08 Google Llc Transformation for machine learning pre-processing
US20210045694A1 (en) * 2019-08-13 2021-02-18 Twin Health, Inc. Precision treatment with machine learning and digital twin technology for optimal metabolic outcomes
US20210142914A1 (en) * 2009-02-09 2021-05-13 Fico Method and system for predicting adherence to a treatment

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210142914A1 (en) * 2009-02-09 2021-05-13 Fico Method and system for predicting adherence to a treatment
US20170209657A1 (en) * 2014-08-01 2017-07-27 Resmed Limited Self-optimising respiratory therapy system
US20170329933A1 (en) * 2016-05-13 2017-11-16 Thomas Edwin Brust Adaptive therapy and health monitoring using personal electronic devices
US20200005929A1 (en) * 2017-03-01 2020-01-02 Ieso Digital Health Limited Psychotherapy Triage Method
US20200320436A1 (en) * 2019-04-08 2020-10-08 Google Llc Transformation for machine learning pre-processing
US20210045694A1 (en) * 2019-08-13 2021-02-18 Twin Health, Inc. Precision treatment with machine learning and digital twin technology for optimal metabolic outcomes

Also Published As

Publication number Publication date
WO2024077103A2 (en) 2024-04-11

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