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OpenAlex Citation Counts

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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:

Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools
Orit Raphaeli, Pierre Singer
Clinical Nutrition (2021) Vol. 40, Iss. 10, pp. 5249-5251
Closed Access | Times Cited: 16

Showing 16 citing articles:

Malnutrition in Hospitalized Old Patients: Screening and Diagnosis, Clinical Outcomes, and Management
Francesco Bellanti, Aurelio Lo Buglio, Stefano Quiete, et al.
Nutrients (2022) Vol. 14, Iss. 4, pp. 910-910
Open Access | Times Cited: 113
Machine Learning in Nutrition Research
Daniel Kirk, E.J. Kok, Michele Tufano, et al.
Advances in Nutrition (2022) Vol. 13, Iss. 6, pp. 2573-2589
Open Access | Times Cited: 73
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
Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach
Md. Moddassir Alam, Asif Irshad Khan, Aasim Zafar, et al.
Brain and Behavior (2025) Vol. 15, Iss. 5
Open Access
The future of artificial intelligence in clinical nutrition
Pierre Singer, Eyal Robinson, Orit Raphaeli
Current Opinion in Clinical Nutrition & Metabolic Care (2023) Vol. 27, Iss. 2, pp. 200-206
Closed Access | Times Cited: 9
Role of Artificial Intelligence in Multinomial Decisions and Preventative Nutrition in Alzheimer's Disease
Ariana Soares Dias Portela, Vrinda Saxena, Eric H. Rosenn, et al.
Molecular Nutrition & Food Research (2024) Vol. 68, Iss. 13
Open Access | Times Cited: 3
A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery
Zakir Hussain, Malaya Dutta Borah
Health Information Science and Systems (2024) Vol. 12, Iss. 1
Closed Access | Times Cited: 2
Enhancing neuro-oncology care through equity-driven applications of artificial intelligence
Mulki Mehari, Youssef Sibih, Abraham Dada, et al.
Neuro-Oncology (2024) Vol. 26, Iss. 11, pp. 1951-1963
Closed Access | Times Cited: 2
Efficient Machine Learning for Malnutrition Prediction among under-five children in India
Saksham Jain, Tayyibah Khanam, Ali Jafar Abedi, et al.
2022 IEEE Delhi Section Conference (DELCON) (2022), pp. 1-10
Closed Access | Times Cited: 11
Clinical and economic value of oral nutrition supplements in patients with cancer: a position paper from the Survivorship Care and Nutritional Support Working Group of Alliance Against Cancer
Riccardo Caccialanza, Alessandro Laviano, Cristina Bosetti, et al.
Supportive Care in Cancer (2022) Vol. 30, Iss. 11, pp. 9667-9679
Closed Access | Times Cited: 11
Implementation of an electronic solution to improve malnutrition identification and support clinical best practice
Sally McCray, Laura Barsha, Kirsty Maunder
Journal of Human Nutrition and Dietetics (2022) Vol. 35, Iss. 6, pp. 1071-1078
Closed Access | Times Cited: 8
Comparison of Nutritional Status Prediction Models of Children Under 5 Years of Age Using Supervised Machine Learning
Mediana Aryuni, Eka Miranda, Meyske Kumbangsila, et al.
Lecture notes in electrical engineering (2023), pp. 265-277
Closed Access | Times Cited: 3
The Determination of a Consensus Nutritional Approach for Cancer Patients in Spain Using the Delphi Methodology
José Pablo Suárez Llanos, Ruth Vera, Jorge Contreras
Nutrients (2022) Vol. 14, Iss. 7, pp. 1404-1404
Open Access | Times Cited: 5
A Novel Machine-Learning Algorithm to Predict the Early Termination of Nutrition Support Team Follow-Up in Hospitalized Adults: A Retrospective Cohort Study
Nadir Yalçın, Merve Kaşıkçı, Burcu Kelleci Çakır, et al.
Nutrients (2024) Vol. 16, Iss. 15, pp. 2492-2492
Open Access
Nutritional treatment in critical patient SARS-CoV-2, view from calm
María Luisa Bordejé, C. Vaquerizo Alonso
Nutrición Hospitalaria (2021)
Open Access | Times Cited: 3
Clinical and economic value of oral nutrition supplements in cancer patients: a position paper from the Survivorship Care and Nutritional Support Working Group of Alliance Against Cancer.
Riccardo Caccialanza, Alessandro Laviano, Cristina Bosetti, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
Digital twins for nutrition
Monireh Vahdati, Ali Mohammad Saghiri, Kamran Gholizadeh HamlAbadi
Elsevier eBooks (2023), pp. 305-323
Closed Access
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