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The American Journal of Clinical Nutrition|January 9, 2025
Early identification of potentially reversible cancer cachexia using explainable machine learning driven by body weight dynamics: a multicenter cohort studyLiangyu Yin, Na Li, Xin Lin, et al.The American Journal of Clinical Nutrition|September 12, 2022
Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challengeLiangyu Yin, Jiuwei Cui, Xin Lin, et al.Journal of Cachexia, Sarcopenia and Muscle|December 25, 2022
Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort studyLiangyu Yin, Jiuwei Cui, Xin Lin, et al.Clinical Nutrition (Edinburgh, Scotland)|August 6, 2021
A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world dataLiangyu Yin, Chunhua Song, Jiuwei Cui, et al.Frontiers in Nutrition|May 2, 2022
<i>De novo</i> Creation and Assessment of a Prognostic Fat-Age-Inflammation Index "FAIN" in Patients With Cancer: A Multicenter Cohort StudyLiangyu Yin, Chunhua Song, Jiuwei Cui, et al.Journal of Cachexia, Sarcopenia and Muscle|February 14, 2025
Diagnostic Criteria for Cancer-Associated Cachexia: Insights from a Multicentre Cohort StudyZhenyu Huo, Feifei Chong, Na Li, et al.Pageof 6