An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups. OBJECTIVE: To evaluate whether clusters identified from baseline pa...

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Detalles Bibliográficos
Autores principales: Xu, Huiwen, Mohamed, Mostafa, Flannery, Marie, Peppone, Luke, Ramsdale, Erika, Loh, Kah Poh, Wells, Megan, Jamieson, Leah, Vogel, Victor G., Hall, Bianca Alexandra, Mustian, Karen, Mohile, Supriya, Culakova, Eva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2023
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034574/
https://www.ncbi.nlm.nih.gov/pubmed/36947036
http://dx.doi.org/10.1001/jamanetworkopen.2023.4198

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034574/
https://www.ncbi.nlm.nih.gov/pubmed/36947036
http://dx.doi.org/10.1001/jamanetworkopen.2023.4198

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