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:

Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review
Yi-Fang Li, Xuetao Wang, Jun Zhang, et al.
Reviews in Endocrine and Metabolic Disorders (2021) Vol. 23, Iss. 3, pp. 387-400
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction‐associated steatotic liver disease – The Gut and Obesity in Asia (GO‐ASIA) Study
Nipun Verma, Ajay Duseja, Manu Mehta, et al.
Alimentary Pharmacology & Therapeutics (2024) Vol. 59, Iss. 6, pp. 774-788
Closed Access | Times Cited: 6
Systematic reviews of machine learning in healthcare: a literature review
Katarzyna Kolasa, Bisrat Yeshewas Admassu, Malwina Hołownia-Voloskova, et al.
Expert Review of Pharmacoeconomics & Outcomes Research (2023) Vol. 24, Iss. 1, pp. 63-115
Open Access | Times Cited: 14
A Machine Learning Model to Predict Risk for Hepatocellular Carcinoma in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease
Souvik Sarkar, Aniket Alurwar, Carole Ly, et al.
Gastro Hep Advances (2024) Vol. 3, Iss. 4, pp. 498-505
Open Access | Times Cited: 5
Revolutionizing MASLD: How Artificial Intelligence Is Shaping the Future of Liver Care
Nicola Pugliese, Arianna Bertazzoni, Cesare Hassan, et al.
Cancers (2025) Vol. 17, Iss. 5, pp. 722-722
Open Access
Diagnostic Accuracy of Convolutional Neural Networks in Classifying Hepatic Steatosis from B-Mode Ultrasound Images: A Systematic Review with Meta-Analysis and Novel Validation in a Community Setting in South India
A B Jagadeesh, Chanchanok Aramrat, Santosh Rai, et al.
(2025)
Closed Access
“Artificial Intelligence in NAFLD Diagnosis: A New Frontier in Managing Metastatic Prostate Cancer Risk”
Zenia Safwan, Hanzala Ahmed Farooqi, Rayyan Nabi
Asia-Pacific Journal of Clinical Oncology (2025)
Closed Access
Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023)
Hamed Zamanian, Ahmad Shalbaf, Mohammad Reza Zali, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 244, pp. 107932-107932
Closed Access | Times Cited: 8
Non-invasive methods to evaluate liver fibrosis in patients with non-alcoholic fatty liver disease
Jincheng Wang, Tao Qin, Jin-Yu Sun, et al.
Frontiers in Physiology (2022) Vol. 13
Open Access | Times Cited: 13
Current Insights and Updates in Ultrasound-Guided Acupuncture: A Comprehensive Review and Status Report
Hongmin Chu, Seongjun Park, Kyungho Kang, et al.
Journal of Korean Medical Society of Acupotomology (2023) Vol. 7, Iss. 2, pp. 121-130
Open Access | Times Cited: 6
Automated machine learning models for nonalcoholic fatty liver disease assessed by controlled attenuation parameter from the NHANES 2017–2020
Lihe Liu, Jiaxi Lin, Lu Liu, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 1
Comparison of Machine Learning Models and the Fatty Liver Index in Predicting Lean Fatty Liver
Pei–Yuan Su, Yang‐Yuan Chen, Chun-Yu Lin, et al.
Diagnostics (2023) Vol. 13, Iss. 8, pp. 1407-1407
Open Access | Times Cited: 4
Artificial Intelligence-Assisted Image Analysis of Acetaminophen-Induced Acute Hepatic Injury in Sprague-Dawley Rats
Eun Bok Baek, Jihee Hwang, Heejin Park, et al.
Diagnostics (2022) Vol. 12, Iss. 6, pp. 1478-1478
Open Access | Times Cited: 7
Artificial intelligence-based ultrasound imaging technologies for hepatic diseases
Longfei Ma, Rui Wang, Qiong He, et al.
iLiver (2022) Vol. 1, Iss. 4, pp. 252-264
Open Access | Times Cited: 6
Systematic Reviews of Machine Learning in Healthcare: A Literature Review
Katarzyna Kolasa, Bisrat Yeshewas Admassu, Malwina Hołownia-Voloskova, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Fibrosis severity scoring on Sirius red histology with multiple-instance deep learning
Sneha N. Naik, Roberta Forlano, Pinelopi Manousou, et al.
Biological Imaging (2023) Vol. 3
Open Access | Times Cited: 2
A data-driven approach to decode metabolic dysfunction-associated steatotic liver disease
Maria Jiménez Ramos, Timothy J. Kendall, Ignat Drozdov, et al.
Annals of Hepatology (2023) Vol. 29, Iss. 2, pp. 101278-101278
Open Access | Times Cited: 2
Artificial intelligence in nonalcoholic fatty liver disease
Ali Mahzari
Egyptian Liver Journal (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 3
Health 4.0 in the medical sector: a narrative review
Antônio Cruz Júnior, Eduardo Mário Dias, Maria Lídia Dias Scoton, et al.
Revista da Associação Médica Brasileira (2024) Vol. 70, Iss. 1
Open Access
Generative AI: A transformative force in advancing research and care in metabolic dysfunction-associated fatty liver disease
Partha Pratim Ray
Liver Research (2024) Vol. 8, Iss. 2, pp. 127-129
Open Access
A systematic review on Artificial Intelligence applied to predictive cardiovascular risk analysis in liver transplantation
N.D. Hirani, Parag Chatterjee
F1000Research (2024) Vol. 13, pp. 701-701
Open Access
Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future
Wenpeng Huang, Yushuo Peng, Lei Kang
View (2024) Vol. 5, Iss. 4
Open Access
Diagnostic Advances in MASLD
Paulina Vidal‐Cevallos, Norberto C. Chávez‐Tapia, Emmanuel Tsochatzis
(2024), pp. 49-60
Closed Access
Future directions for fatty liver disease
Anna Di Bartolomeo, Jacob George
Elsevier eBooks (2024), pp. 297-317
Closed Access
Noninvasive, serum-based evaluation of liver fibrosis in metabolic (dysfunction)-associated fatty liver disease
Eda Kaya, Yusuf Yılmaz
Elsevier eBooks (2024), pp. 137-150
Closed Access
The global research of artificial intelligence on metabolic dysfunction-associated fatty liver disease: a bibliometric analysis (Preprint)
Yumei Huang, Mengpei Zhu, Ziwen Wang, et al.
(2023)
Closed Access | Times Cited: 1
Page 1 - Next Page

Scroll to top