Area of research
Physiology · Geriatrics and Gerontology
Research interest
Research interests include Medicine, Internal medicine, Cancer, Cachexia, Malnutrition, and Cohort.
Early identification of potentially reversible cancer cachexia using explainable machine learning driven by body weight dynamics: a multicenter cohort study
Diagnostic Criteria for Cancer‐Associated Cachexia: Insights from a Multicentre Cohort Study
Corrigendum to “Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge” Am J Clin Nutr 116 (2022) 1229–1239
Explainable deep learning model WAL-net for individualised assessment of potentially reversible malnutrition in patients with cancer: a multicentre cohort study
Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
Value of the modified Patient‐Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs
Exploring the optimal indicator of short‐term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study
Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study
Ensemble learning system to identify nutritional risk and malnutrition in cancer patients without weight loss information
Comment on: “Triceps skinfold‐albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study” by Yin et al. ‐ the authors reply
Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge
Triceps skinfold–albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study
De novo Creation and Assessment of a Prognostic Fat-Age-Inflammation Index “FAIN” in Patients With Cancer: A Multicenter Cohort Study
A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data
Is hand grip strength a necessary supportive index in the phenotypic criteria of the GLIM-based diagnosis of malnutrition in patients with cancer?
The role and possible mechanism of lncRNA U90926 in modulating 3T3-L1 preadipocyte differentiation