Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review

Sanam Tabataba Vakili¹, Darren Haywood², Deborah Kirk^{3

4}, Aalaa M Abdou⁵, Ragisha Gopalakrishnan^{6

7}, Sarina Sadeghi¹, Helena Guedes⁸, Chia Jie Tan⁹, Carla Thamm¹⁰, Rhys Bernard¹¹, Henry C Y Wong¹², Elaine P Kuhn^{13

14}, Jennifer Y Y Kwan¹⁵, Shing Fung Lee¹⁶, Nicolas H Hart^{2

10

17}, Catherine Paterson¹⁰, Deepti A Chopra¹⁸, Amanda Drury¹⁹, Elwyn Zhang¹, Shayan Raeisi Dehkordi²⁰, Fredrick D Ashbury^{21

22

23}, Grigorios Kotronoulas²⁴, Edward Chow¹⁵, Michael Jefford²⁵, Raymond J Chan¹⁰, Rouhi Fazelzad²⁶, Srinivas Raman²⁷, Muna Alkhaifi¹; Multinational Association of Supportive Care in Cancer (MASCC) Survivorship Study Group

Affiliations

¹ Department of Medical Oncology & Hematology, Odette Cancer Centre, Sunnybrook Health Science Centre, Toronto, ON, Canada.
² Human Performance Research Centre, INSIGHT Research Institute, University of Technology Sydney (UTS), Sydney, NSW, Australia.
³ School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia.
⁴ School of Nursing and Midwifery, Edith Cowan University, Perth, WA, Australia.
⁵ Elzaitoun Specialized Hospital, Ministry of Health and Population, Amreya, Egypt.
⁶ Mount Sinai Medical Center, Miami, FL.
⁷ Columbia Irving Cancer Center, New York, NY.
⁸ Medical Oncology Department, Unidade Local de Saúde Gaia Espinho, Porto, Portugal.
⁹ Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT.
¹⁰ Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, Australia.
¹¹ McMaster University, Health Sciences, Hamilton, ON, Canada.
¹² Department of Oncology, Princess Margaret Hospital, Kowloon West Cluster, Hong Kong S.A.R., China.
¹³ Dartmouth-Hitchcock Medical Center, Lebanon, NH.
¹⁴ Geisel School of Medicine, Hanover, NH.
¹⁵ Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.
¹⁶ Department of Radiation Oncology, National University Cancer Institute, National University Hospital, Singapore, Singapore.
¹⁷ Exercise Medicine Research Institute, School of Medical and Health Science, Edith Cowan University, Perth, WA, Australia.
¹⁸ Department of Psychiatry, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX.
¹⁹ School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland.
²⁰ Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
²¹ Department of Oncology, University of Calgary, AB, Canada.
²² Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH.
²³ Clinical & Scientific Division, VieCure, Denver, CO.
²⁴ School of Medicine Dentistry and Nursing, University of Glasgow, Glasgow, the United Kingdom.
²⁵ Department of Health Services Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
²⁶ Library and Information Services, University Health Network- Princess Margaret Cancer Centre, Toronto, ON, Canada.
²⁷ Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada.

PMID: 39621952
DOI: 10.1200/CCI.24.00119

Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review

Sanam Tabataba Vakili et al. JCO Clin Cancer Inform. 2024 Dec.

. 2024 Dec:8:e2400119.

doi: 10.1200/CCI.24.00119. Epub 2024 Dec 2.

Authors

Affiliations

¹ Department of Medical Oncology & Hematology, Odette Cancer Centre, Sunnybrook Health Science Centre, Toronto, ON, Canada.
² Human Performance Research Centre, INSIGHT Research Institute, University of Technology Sydney (UTS), Sydney, NSW, Australia.
³ School of Nursing and Midwifery, La Trobe University, Melbourne, VIC, Australia.
⁴ School of Nursing and Midwifery, Edith Cowan University, Perth, WA, Australia.
⁵ Elzaitoun Specialized Hospital, Ministry of Health and Population, Amreya, Egypt.
⁶ Mount Sinai Medical Center, Miami, FL.
⁷ Columbia Irving Cancer Center, New York, NY.
⁸ Medical Oncology Department, Unidade Local de Saúde Gaia Espinho, Porto, Portugal.
⁹ Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT.
¹⁰ Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, Australia.
¹¹ McMaster University, Health Sciences, Hamilton, ON, Canada.
¹² Department of Oncology, Princess Margaret Hospital, Kowloon West Cluster, Hong Kong S.A.R., China.
¹³ Dartmouth-Hitchcock Medical Center, Lebanon, NH.
¹⁴ Geisel School of Medicine, Hanover, NH.
¹⁵ Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.
¹⁶ Department of Radiation Oncology, National University Cancer Institute, National University Hospital, Singapore, Singapore.
¹⁷ Exercise Medicine Research Institute, School of Medical and Health Science, Edith Cowan University, Perth, WA, Australia.
¹⁸ Department of Psychiatry, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX.
¹⁹ School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland.
²⁰ Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
²¹ Department of Oncology, University of Calgary, AB, Canada.
²² Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH.
²³ Clinical & Scientific Division, VieCure, Denver, CO.
²⁴ School of Medicine Dentistry and Nursing, University of Glasgow, Glasgow, the United Kingdom.
²⁵ Department of Health Services Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
²⁶ Library and Information Services, University Health Network- Princess Margaret Cancer Centre, Toronto, ON, Canada.
²⁷ Department of Radiation Oncology, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada.

PMID: 39621952
DOI: 10.1200/CCI.24.00119

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 = 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.

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Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review

Affiliations

Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review

Authors

Affiliations

Abstract

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Medical

Miscellaneous