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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:

Machine Learning Solutions for Osteoporosis—A Review
Julien Smets, Enisa Shevroja, Thomas Hügle, et al.
Journal of Bone and Mineral Research (2020) Vol. 36, Iss. 5, pp. 833-851
Open Access | Times Cited: 125

Showing 1-25 of 125 citing articles:

Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis
Rachel Kuo, Conrad Harrison, Terry‐Ann Curran, et al.
Radiology (2022) Vol. 304, Iss. 1, pp. 50-62
Open Access | Times Cited: 156
ChatGPT: when artificial intelligence replaces the rheumatologist in medical writing
Frank Verhoeven, Daniel Wendling, Clément Prati
Annals of the Rheumatic Diseases (2023) Vol. 82, Iss. 8, pp. 1015-1017
Open Access | Times Cited: 44
How AI May Transform Musculoskeletal Imaging
Ali Guermazi, Patrick Omoumi, Mickaël Tordjman, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 16
A simple and user-friendly machine learning model to detect osteoporosis in health examination populations in Southern Taiwan
Wei‐Chin Huang, I-Shu Chen, Hsien‐Chung Yu, et al.
Bone Reports (2025) Vol. 24, pp. 101826-101826
Open Access | Times Cited: 2
Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning
Chen-I Hsieh, Kang Zheng, Chi‐Hung Lin, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 100
Risk assessment tools for osteoporosis and fractures in 2022
John Carey, Paulo Chih-Hsing Wu, Diane Bergin
Best Practice & Research Clinical Rheumatology (2022) Vol. 36, Iss. 3, pp. 101775-101775
Closed Access | Times Cited: 59
A pilot study of a deep learning approach to detect marginal bone loss around implants
Min Liu, Wang Shi-min, Chen Hu, et al.
BMC Oral Health (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 41
Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data
Junbo Tu, Weijie Liao, Wencai Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 14
Muscle parameters in fragility fracture risk prediction in older adults: A scoping review
Colin Vendrami, Enisa Shevroja, Elena González Rodríguez, et al.
Journal of Cachexia Sarcopenia and Muscle (2024) Vol. 15, Iss. 2, pp. 477-500
Open Access | Times Cited: 10
A Review on the Use of Artificial Intelligence in Fracture Detection
Aayushi Bhatnagar, Aditya Kekatpure, Vivek R Velagala, et al.
Cureus (2024)
Open Access | Times Cited: 9
Artificial Intelligence-enabled Chest X-ray Classifies Osteoporosis and Identifies Mortality Risk
Dung-Jang Tsai, Chin Lin, Chin‐Sheng Lin, et al.
Journal of Medical Systems (2024) Vol. 48, Iss. 1
Closed Access | Times Cited: 8
Deep Learning for Bone Mineral Density and T-Score Prediction from Chest X-rays: A Multicenter Study
Yoichi Sato, Norio Yamamoto, Naoya Inagaki, et al.
Biomedicines (2022) Vol. 10, Iss. 9, pp. 2323-2323
Open Access | Times Cited: 37
Osteoporosis Screening: Applied Methods and Technological Trends
Mario De Oliveira, Raimes Moraes, Everton B. Castanha, et al.
Medical Engineering & Physics (2022) Vol. 108, pp. 103887-103887
Open Access | Times Cited: 32
Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography
Yung-Chieh Chen, Yi-Tien Li, Po‐Chih Kuo, et al.
European Radiology (2023) Vol. 33, Iss. 7, pp. 5097-5106
Closed Access | Times Cited: 20
Using Artificial Intelligence to Diagnose Osteoporotic Vertebral Fractures on Plain Radiographs
Li Shen, Chao Gao, Shundong Hu, et al.
Journal of Bone and Mineral Research (2023) Vol. 38, Iss. 9, pp. 1278-1287
Open Access | Times Cited: 20
A decision support system for osteoporosis risk prediction using machine learning and explainable artificial intelligence
Varada Vivek Khanna, Krishnaraj Chadaga, Niranjana Sampathila, et al.
Heliyon (2023) Vol. 9, Iss. 12, pp. e22456-e22456
Open Access | Times Cited: 20
New tools for bone health assessment in secreting pituitary adenomas
Meliha Melin Uygur, Stefano Frara, Luigi di Filippo, et al.
Trends in Endocrinology and Metabolism (2023) Vol. 34, Iss. 4, pp. 231-242
Closed Access | Times Cited: 17
A Comprehensive Analysis of Artificial Intelligence Techniques for the Prediction and Prognosis of Lifestyle Diseases
Krishna Modi, Ishbir Singh, Yogesh Kumar
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 8, pp. 4733-4756
Closed Access | Times Cited: 16
Osteoporosis screening using machine learning and electromagnetic waves
Gabriela A. Albuquerque, Dionísio D. A. Carvalho, Agnaldo S. Cruz, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 16
Application of Deep Convolutional Neural Networks in the Diagnosis of Osteoporosis
Róża Dzierżak, Zbigniew Omiotek
Sensors (2022) Vol. 22, Iss. 21, pp. 8189-8189
Open Access | Times Cited: 23
Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation
Bogyeong Suh, Heejin Yu, Hye‐Yeon Kim, et al.
Journal of Medical Internet Research (2022) Vol. 25, pp. e40179-e40179
Open Access | Times Cited: 22
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
Understanding the role and adoption of artificial intelligence techniques in rheumatology research: An in-depth review of the literature
Alfredo Madrid-García, Beatriz Merino‐Barbancho, Alejandro Rodríguez‐González, et al.
Seminars in Arthritis and Rheumatism (2023) Vol. 61, pp. 152213-152213
Open Access | Times Cited: 13
Diagnosis and therapeutic approach to bone health in patients with hypopituitarism
Justyna Kuliczkowska-Płaksej, Aleksandra Zdrojowy-Wełna, Aleksandra Jawiarczyk-Przybyłowska, et al.
Reviews in Endocrine and Metabolic Disorders (2024) Vol. 25, Iss. 3, pp. 513-539
Closed Access | Times Cited: 5
Application of ChatGPT-4 to oculomics: a cost-effective osteoporosis risk assessment to enhance management as a proof-of-principles model in 3PM
Joon Yul Choi, Eoksoo Han, Tae Keun Yoo
The EPMA Journal (2024) Vol. 15, Iss. 4, pp. 659-676
Closed Access | Times Cited: 4
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