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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:

Explainable machine learning model for predicting the occurrence of postoperative malnutrition in children with congenital heart disease
Hui Shi, Dong Yang, Kaichen Tang, et al.
Clinical Nutrition (2021) Vol. 41, Iss. 1, pp. 202-210
Closed Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Hui Wen Loh, Chui Ping Ooi, Silvia Seoni, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107161-107161
Open Access | Times Cited: 433
Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations
Alexander A. Huang, Samuel Y. Huang
PLoS ONE (2023) Vol. 18, Iss. 2, pp. e0281922-e0281922
Open Access | Times Cited: 54
Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer
Wen‐Han Hsu, A.-R. Ko, Chia‐Sui Weng, et al.
Journal of Cachexia Sarcopenia and Muscle (2023) Vol. 14, Iss. 5, pp. 2044-2053
Open Access | Times Cited: 17
A comprehensive review for chronic disease prediction using machine learning algorithms
Rakibul Islam, Azrin Sultana, Mohammad Rashedul Islam
Journal of Electrical Systems and Information Technology (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 8
XAI-based Clinical Decision Support System: A Systematic Review
SeYoung Kim, Daeho Kim, Minji Kim, et al.
(2024)
Open Access | Times Cited: 6
Artificial Intelligence in Pediatric Cardiology: A Scoping Review
Yashendra Sethi, Neil Patel, Nirja Kaka, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 23, pp. 7072-7072
Open Access | Times Cited: 24
eXplainable Artificial Intelligence (XAI) for improving organisational regility
Niusha Shafiabady, Nick Hadjinicolaou, Nadeesha D. Hettikankanamage, et al.
PLoS ONE (2024) Vol. 19, Iss. 4, pp. e0301429-e0301429
Open Access | Times Cited: 5
A review of evaluation approaches for explainable AI with applications in cardiology
Ahmed Salih, Ilaria Boscolo Galazzo, Polyxeni Gkontra, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 9
Open Access | Times Cited: 5
XAI-Based Clinical Decision Support Systems: A Systematic Review
Se Young Kim, Dae Ho Kim, Min‐Ji Kim, et al.
Applied Sciences (2024) Vol. 14, Iss. 15, pp. 6638-6638
Open Access | Times Cited: 4
Detección de Desnutrición Crónica en Niños Menores a Cinco Años Aplicando Técnicas Multivariantes
Dennys Daquilema, Erick Herrera
INNOVATION & DEVELOPMENT IN ENGINEERING AND APPLIED SCIENCES (2025) Vol. 7, Iss. 1, pp. 25-25
Closed Access
Explainable machine learning model for predicting decline in platelet count after interventional closure in children with patent ductus arteriosus
Songyue Zhang, Yidong Zhang, Hao Li, et al.
Frontiers in Pediatrics (2025) Vol. 13
Open Access
Explainable machine learning model for predicting paratracheal lymph node metastasis in cN0 papillary thyroid cancer
Lin Chun, Denghuan Wang, Liqiong He, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Machine learning framework for evaluating fracturing-flooding effectiveness: From prediction to decision recommendations
Xiang Wang, Xianxiang Chu, Yixin Xie, et al.
Fuel (2024) Vol. 381, pp. 133299-133299
Closed Access | Times Cited: 3
Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus
Zhuoyang Li, Yuqian Li, Zhenxing Mao, et al.
Nutrients (2025) Vol. 17, Iss. 6, pp. 947-947
Open Access
The Impact of Household Resilience and Dietary Diversity on Child Malnutrition
Licong Xing, Shahla Akram, Mehboob Ul Hassan, et al.
Health & Social Care in the Community (2025) Vol. 2025, Iss. 1
Open Access
Predicting postoperative malnutrition in patients with oral cancer: development of an XGBoost model with SHAP analysis and web-based application
Lixia Kuang, Jingya Yu, Yunyu Zhou, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access
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
Explainable AI for malnutrition risk prediction from m-Health and clinical data
Flavio Di Martino, Franca Delmastro, Cristina Dolciotti
Smart Health (2023) Vol. 30, pp. 100429-100429
Open Access | Times Cited: 7
Explainable machine learning-assisted origin identification: Chemical profiling of five lotus (Nelumbo nucifera Gaertn.) parts
Jingxian Huang, Zhen Li, Wei Zhang, et al.
Food Chemistry (2022) Vol. 404, pp. 134517-134517
Closed Access | Times Cited: 12
Can Unmanned Aerial Vehicle Images Be Used to Estimate Forage Production Parameters in Agroforestry Systems in the Caatinga?
Wagner Martins dos Santos, Claudenilde de Jesus Pinheiro Costa, M. Medeiros, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4896-4896
Open Access | Times Cited: 2
Recognizing and Predicting the Risk of Malnutrition in the Elderly Using Artificial Intelligence: A Systematic Review
Joyeta Ghosh
International Journal of Advancement in Life Sciences Research (2024) Vol. 07, Iss. 03, pp. 01-14
Open Access | Times Cited: 2
The application of explainable artificial intelligence (XAI) in electronic health record research: A scoping review
Jessica Caterson, Alex Lewin, Elizabeth Williamson
Digital Health (2024) Vol. 10
Open Access | Times Cited: 2
Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review
Ida Mohammadi, Sharyar Rajai Firouzabadi, Melika Hosseinpour, et al.
BMC Cardiovascular Disorders (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
A risk prediction model based on machine learning for postoperative cognitive dysfunction in elderly patients with non-cardiac surgery
Xianhai Xie, Junlin Li, Yi Zhong, et al.
Aging Clinical and Experimental Research (2023) Vol. 35, Iss. 12, pp. 2951-2960
Closed Access | Times Cited: 5
Development and evaluation of a deep learning framework for the diagnosis of malnutrition using a 3D facial points cloud: A cross‐sectional study
Xue Wang, Yan Liu, Zhiqin Rong, et al.
Journal of Parenteral and Enteral Nutrition (2024) Vol. 48, Iss. 5, pp. 554-561
Closed Access | Times Cited: 1
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