Novel bayesian nonparametric unsupervised learning approach to precision symptom management in cancer survivors: a re-analysis of a comparative effectiveness trial.

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Bibliographic Details
Title: Novel bayesian nonparametric unsupervised learning approach to precision symptom management in cancer survivors: a re-analysis of a comparative effectiveness trial.
Authors: Li Y; Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 633 3rd Avenue, New York, NY, 10017, USA. liy12@mskcc.org.; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. liy12@mskcc.org., Liou KT; Integrative Medicine Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Schofield E; Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 633 3rd Avenue, New York, NY, 10017, USA., Atkinson TM; Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, 633 3rd Avenue, New York, NY, 10017, USA., Mao JJ; Integrative Medicine Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Source: Journal of behavioral medicine [J Behav Med] 2026 Apr; Vol. 49 (2), pp. 372-385. Date of Electronic Publication: 2026 Jan 23.
Publication Type: Journal Article
Journal Info: Publisher: Springer Science + Business Media Country of Publication: United States NLM ID: 7807105 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-3521 (Electronic) Linking ISSN: 01607715 NLM ISO Abbreviation: J Behav Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-3521
DOI:10.1007/s10865-025-00621-7