METHODS AND APPARATUS FOR MACHINE LEARNING TO CALCULATE A PATIENT BURDEN SCORE FOR PARTICIPATION IN A CLINICAL TRIAL

METHODS AND APPARATUS FOR MACHINE LEARNING TO CALCULATE A PATIENT BURDEN SCORE FOR PARTICIPATION IN A CLINICAL TRIAL

Disclosed herein are methods and systems to predict and quantify a patient's burden when participating in a clinical trial. A method includes gathering data associated with pervious participants and their burden and experiences when participating in clinical trials. The method also includes exe...

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Bibliographische Detailangaben
Hauptverfasser: BAGGA, Abhishek, OLAH, Zachary, CARNEY, Christopher, GROVE, Nicholl
Format: Patent
Sprache:eng
Schlagworte:
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Beschreibung
Zusammenfassung:Disclosed herein are methods and systems to predict and quantify a patient's burden when participating in a clinical trial. A method includes gathering data associated with pervious participants and their burden and experiences when participating in clinical trials. The method also includes executing data clean-up protocols to quantify and standardize the previous participants' experiences and burden. The method then includes training one or more computer models to identify connections between participants and their unique attributes in light of their standardized burden and to predict a patient burden score for a new patient participating in a new clinical trial.