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Discovery of distinct cancer cachexia phenotypes using an unsupervised machine-learning algorithm.

Nutrition (Burbank, Los Angeles County, Calif.) - 1 Mar 2024

Wu Hao-Fan, Yan Jiang-Peng, Wu Qian, Yu Zhen, Xu Hong-Xia, Song Chun-Hua, Guo Zeng-Qing, Li Wei, Xiang Yan-Jun, Xu Zhe, Luo Jie, Cheng Shu-Qun, Zhang Feng-Min, Shi Han-Ping, Zhuang Cheng-Le

Abstract excerpt

OBJECTIVES: Cancer cachexia is a debilitating condition with widespread negative effects. The heterogeneity of clinical features within patients with cancer cachexia is unclear. The identification and prognostic analysis of diverse phenotypes of cancer cachexia may help develop individualized interventions to improve outcomes for vulnerable populations. The aim of this study was to show that the machine...

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PMID: 38154396
DOI: 10.1016/j.nut.2023.112317

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