Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review.

Journal: Health and quality of life outcomes

PMID: 40217230

Abstract

PURPOSE: This scoping review aims to identify and summarise artificial intelligence (AI) methods applied to patient-reported outcome measures (PROMs) for prediction of patient outcomes, such as survival, quality of life, or treatment decisions.

Authors

Zuzanna Wójcik

UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care, University of Leeds, Leeds, United Kingdom.
Vania Dimitrova

School of Computing, University of Leeds, Leeds, United Kingdom.
Lorraine Warrington

Leeds Institute of Medical Research, University of Leeds, St James's University Hospital, Leeds, United Kingdom.
Galina Velikova

Leeds Institute of Medical Research, University of Leeds, St James's University Hospital, Leeds, United Kingdom.
Kate Absolom

Leeds Institute of Medical Research, University of Leeds, St James's University Hospital, Leeds, United Kingdom.

Keywords

Artificial Intelligence Humans Patient Reported Outcome Measures Quality of Life

External Resources

View on PubMed Access via DOI PubMed (40217230)

Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review.

Abstract

Authors

Keywords

External Resources

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