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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:

Screening for Osteoporosis from Blood Test Data in Elderly Women Using a Machine Learning Approach
Atsuyuki Inui, Hanako Nishimoto, Yutaka Mifune, et al.
Bioengineering (2023) Vol. 10, Iss. 3, pp. 277-277
Open Access | Times Cited: 11

Showing 11 citing articles:

Machine Learning-Based 28-Day Mortality Prediction Model for Elderly Neurocritically Ill Patients
Jia Yuan, Jiong Xiong, Jinfeng Yang, et al.
Computer Methods and Programs in Biomedicine (2025) Vol. 260, pp. 108589-108589
Open Access
Ensemble-learning approach improves fracture prediction using genomic and phenotypic data
Qing Wu, Jong-Yun Jung
Osteoporosis International (2025)
Open Access
Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women
Minkyung Je, Seunghyeon Hwang, Suwon Lee, et al.
BMC Women s Health (2025) Vol. 25, Iss. 1
Open Access
Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3–5 and end-stage kidney disease
Chia‐Tien Hsu, Chin‐Yin Huang, Cheng‐Hsu Chen, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Re-tear after arthroscopic rotator cuff tear surgery: risk analysis using machine learning
Issei Shinohara, Yutaka Mifune, Atsuyuki Inui, et al.
Journal of Shoulder and Elbow Surgery (2023) Vol. 33, Iss. 4, pp. 815-822
Closed Access | Times Cited: 10
Application of Machine Learning Algorithms to Predict Osteoporotic Fractures in Women
Su Jeong Kang, Moon Jong Kim, Yang‐Im Hur, et al.
Korean Journal of Family Medicine (2024) Vol. 45, Iss. 3, pp. 144-148
Open Access | Times Cited: 3
Digital infrared thermography and machine learning for diabetic foot assessment: thermal patterns and classification
Rogelio Castillo-Morquecho, Edgar Guevara, José L. Ramírez-GarcíaLuna, et al.
Journal of Diabetes & Metabolic Disorders (2024) Vol. 23, Iss. 2, pp. 1967-1976
Closed Access | Times Cited: 2
A diagnostic approach integrated multimodal radiomics with machine learning models based on lumbar spine CT and X-ray for osteoporosis
Liwei Cheng, Fangqi Cai, Mingzhi Xu, et al.
Journal of Bone and Mineral Metabolism (2023) Vol. 41, Iss. 6, pp. 877-889
Closed Access | Times Cited: 6
Machine Learning Algorithm Predicts Mortality Risk in Intensive Care Unit for Patients with Traumatic Brain Injury
Kuan-Chi Tu, Eric nyam tee Tau, Nai-Ching Chen, et al.
Diagnostics (2023) Vol. 13, Iss. 18, pp. 3016-3016
Open Access | Times Cited: 4
Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification
Su Jeong Kang, Joung Ouk Kim, Moon Jong Kim, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Featured Papers in Computer Methods in Biomedicine
Luca Mesin
Bioengineering (2024) Vol. 11, Iss. 10, pp. 985-985
Open Access
Posture Estimation Model Combined With Machine Learning Estimates the Radial Abduction Angle of the Thumb With High Accuracy
Issei Shinohara, Atsuyuki Inui, Yutaka Mifune, et al.
Cureus (2024)
Open Access
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