Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Classification Tree–Based Machine Learning to Visualize and Validate a Decision Tool for Identifying Malnutrition in Cancer Patients
Liangyu Yin, Xin Lin, Jie Liu, et al.
Journal of Parenteral and Enteral Nutrition (2021) Vol. 45, Iss. 8, pp. 1736-1748
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition (GLIM) diagnosis of malnutrition
Rocco Barazzoni, Gordon L. Jensen, María Isabel Toulson Davisson Correia, et al.
Clinical Nutrition (2022) Vol. 41, Iss. 6, pp. 1425-1433
Open Access | Times Cited: 220
Utilization and validation of the Global Leadership Initiative on Malnutrition (GLIM): A scoping review
María Isabel Toulson Davisson Correia, Kelly A. Tappenden, Ainsley Malone, et al.
Clinical Nutrition (2022) Vol. 41, Iss. 3, pp. 687-697
Open Access | Times Cited: 72
Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition diagnosis of malnutrition
Charlene Compher, Tommy Cederholm, María Isabel Toulson Davisson Correia, et al.
Journal of Parenteral and Enteral Nutrition (2022) Vol. 46, Iss. 6, pp. 1232-1242
Open Access | Times Cited: 69
Association of Malnutrition, as Defined by the PG-SGA, ESPEN 2015, and GLIM Criteria, With Complications in Esophageal Cancer Patients After Esophagectomy
Liangyu Yin, Nian Cheng, Ping Chen, et al.
Frontiers in Nutrition (2021) Vol. 8
Open Access | Times Cited: 60
Impact of malnutrition as defined by the GLIM criteria on treatment outcomes in patients with cancer: A systematic review and meta-analysis
Ryota Matsui, Kazuma Rifu, Jun Watanabe, et al.
Clinical Nutrition (2023) Vol. 42, Iss. 5, pp. 615-624
Closed Access | Times Cited: 37
Role of artificial intelligence in predicting disease-related malnutrition - A narrative review
Daniel Antonio de Luis, Juan José López Gómez, David E. Barajas Galindo, et al.
Nutrición Hospitalaria (2025)
Open Access | Times Cited: 1
GLIM‐defined malnutrition and overall survival in cancer patients: A meta‐analysis
Liangyu Yin, Feifei Chong, Zhenyu Huo, et al.
Journal of Parenteral and Enteral Nutrition (2022) Vol. 47, Iss. 2, pp. 207-219
Open Access | Times Cited: 30
Artificial Intelligence in Malnutrition: A Systematic Literature Review
Sander M W Janssen, Yamine Bouzembrak, Bedir Teki̇nerdoğan
Advances in Nutrition (2024) Vol. 15, Iss. 9, pp. 100264-100264
Open Access | Times Cited: 6
A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data
Liangyu Yin, Chunhua Song, Jiuwei Cui, et al.
Clinical Nutrition (2021) Vol. 40, Iss. 8, pp. 4958-4970
Closed Access | Times Cited: 40
Prevalence of malnutrition based on global leadership initiative in malnutrition criteria for completeness of diagnosis and future risk of malnutrition based on current malnutrition diagnosis: systematic review and meta-analysis
Wentao Bian, Yi Li, Yu Wang, et al.
Frontiers in Nutrition (2023) Vol. 10
Open Access | Times Cited: 16
Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
Liangyu Yin, Chunhua Song, Jiuwei Cui, et al.
The journal of nutrition health & aging (2024) Vol. 28, Iss. 1, pp. 100023-100023
Open Access | Times Cited: 5
Research progress on predictive models for malnutrition in cancer patients
Pengcheng Zheng, Bo Wang, Yan Luo, et al.
Frontiers in Nutrition (2024) Vol. 11
Open Access | Times Cited: 5
A scoping review on the GLIM criteria for malnutrition diagnosis: Understanding how and for which purpose it has been applied in studies on hospital settings
Danielle Silla Jobim Milanez, Elisa Loch Razzera, Ingrid da Silveira Knobloch, et al.
Clinical Nutrition (2022) Vol. 42, Iss. 1, pp. 29-44
Closed Access | Times Cited: 19
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
Zhenyu Huo, Feifei Chong, Liangyu Yin, et al.
Clinical Nutrition (2023) Vol. 42, Iss. 6, pp. 1048-1058
Closed Access | Times Cited: 11
Diagnostic performance of GLIM and PG-SGA for malnutrition assessment in adult cancer patients: a systematic review and meta-analysis
Jielin Zhou, Shoumei Yang, Ting Liu, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Global Leadership Initiative on Malnutrition criteria as a nutrition assessment tool for patients with cancer
Kang‐Ping Zhang, Meng Tang, Zhenming Fu, et al.
Nutrition (2021) Vol. 91-92, pp. 111379-111379
Closed Access | Times Cited: 27
Malnutrition Diagnosed by Patient‐Generated Subjective Global Assessment and the Risk of All‐Cause Mortality in Adults With Gastrointestinal Cancer: A Systematic Review and Meta‐Analysis
Awole Seid, Zelalem Debebe, Abebe Ayelign, et al.
Journal of Human Nutrition and Dietetics (2025) Vol. 38, Iss. 1
Closed Access
Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia
Chengyu Liu, Hongyun Huang, Moxi Chen, et al.
Aging Clinical and Experimental Research (2025) Vol. 37, Iss. 1
Open Access
Artificial Intelligence in the Management of Malnutrition in Cancer Patients: A Systematic Review
Marco Sguanci, Sara Morales Palomares, Giovanni Cangelosi, et al.
Advances in Nutrition (2025), pp. 100438-100438
Open Access
Fat mass assessment using the triceps skinfold thickness enhances the prognostic value of the Global Leadership Initiative on Malnutrition criteria in patients with lung cancer
Liangyu Yin, Fan Yang, Xin Lin, et al.
British Journal Of Nutrition (2021) Vol. 127, Iss. 10, pp. 1506-1516
Closed Access | Times Cited: 23
Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge
Liangyu Yin, Jiuwei Cui, Xin Lin, et al.
American Journal of Clinical Nutrition (2022) Vol. 116, Iss. 5, pp. 1229-1239
Open Access | Times Cited: 16
Development and Assessment of Assisted Diagnosis Models Using Machine Learning for Identifying Elderly Patients With Malnutrition: Cohort Study
Xue Wang, Fengchun Yang, Mingwei Zhu, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e42435-e42435
Open Access | Times Cited: 9
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
Feifei Chong, Zhenyu Huo, Liangyu Yin, et al.
Nutrition in Clinical Practice (2024) Vol. 39, Iss. 4, pp. 920-933
Closed Access | Times Cited: 3
Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach
Ran Duan, QingYuan Li, Qing Yuan, et al.
Geriatric Nursing (2024) Vol. 58, pp. 388-398
Closed Access | Times Cited: 3
Construction of individualised care programmes for patients with pancreatic cancer with postoperative weight-loss control based on the Delphi method: a cross-sectional study in China
Leying Chen, Zhongyan Huang, Qiuju Tian, et al.
Journal of Health Population and Nutrition (2024) Vol. 43, Iss. 1
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top