Application of artificial intelligence in symptom monitoring in adult cancer survivorship: A systematic review
Author Identifier
Nicolas H. Hart: https://orcid.org/0000-0003-2794-0193
Document Type
Journal Article
Publication Title
JCO Clinical Cancer Informatics
Volume
8
PubMed ID
39621952
Publisher
American Society of Clinical Oncology
School
School of Nursing and Midwifery / Exercise Medicine Research Institute / School of Medical and Health Sciences
RAS ID
77095
Funders
National Health and Medical Research Council / MASCC Cognition Fellowship
Grant Number
NHMRC Numbers : APP1194051, APP2018070
Abstract
PURPOSE The adoption of artificial intelligence (AI) in health care may afford new avenues for personalized and patient-centered care. This systematic review explored the role of AI in symptom monitoring for adult cancer survivors. METHODS A comprehensive search was performed from inception to November 2023 in seven bibliographic databases and three clinical trial registries. This PROSPERO registered review (ID: CRD42023476027) assessed reports of empirical research studies of AI use in symptom monitoring (physical and psychological symptoms) across all cancer types in adults. RESULTS A total of 18,530 reports were identified, of which 41 met review criteria and were analyzed. Included studies were predominantly published between 2021 and 2023, originated in the United States (39.0%) and Japan (14.6%), and primarily used cohort designs (80.5%), followed by cross-sectional designs (12.2%). The mean sample size was 617.14 (standard deviation 5 1,401.37), with most studies primarily including multiple tumor types (31.7%) or breast cancer survivors (26.8%). Machine learning algorithms (43.9%) was the most used AI method, followed by natural language processing (29.3%), AI-driven chatbots (17.1%), and decision support tools (9.8%). The most common inputs to the AI algorithms were textual data, patient-reported symptoms, and physiologic measurements. The most examined symptom was pain (34.2% of studies), followed by fatigue and nausea (17.1% of studies each). Overall, the review showed increasing AI technology use in the prediction and monitoring of cancer symptoms. CONCLUSION AI is being used to enhance symptom monitoring in various cancer settings. When considering integration into clinical practice, standardization of data capture, the use of analytics, investing in infrastructure, and the end-user experience should be considered for successful implementation and monitoring the improvement of patient outcomes.
DOI
10.1200/CCI.24.00119
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Comments
Tabataba Vakili, S., Haywood, D., Kirk, D., Abdou, A. M., Gopalakrishnan, R., Sadeghi, S., ... & Multinational Association of Supportive Care in Cancer (MASCC) Survivorship Study Group. (2024). Application of artificial intelligence in symptom monitoring in adult cancer survivorship: A systematic review. JCO Clinical Cancer Informatics, 8. https://doi.org/10.1200/CCI.24.00119