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:
Chest radiography as a biomarker of ageing: artificial intelligence-based, multi-institutional model development and validation in Japan
Yasuhito Mitsuyama, Toshimasa Matsumoto, Hiroyuki Tatekawa, et al.
The Lancet Healthy Longevity (2023) Vol. 4, Iss. 9, pp. e478-e486
Open Access | Times Cited: 12
Yasuhito Mitsuyama, Toshimasa Matsumoto, Hiroyuki Tatekawa, et al.
The Lancet Healthy Longevity (2023) Vol. 4, Iss. 9, pp. e478-e486
Open Access | Times Cited: 12
Showing 12 citing articles:
Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future
Daiju Ueda, Shannon L. Walston, Shohei Fujita, et al.
Diagnostic and Interventional Imaging (2024) Vol. 105, Iss. 11, pp. 453-459
Open Access | Times Cited: 16
Daiju Ueda, Shannon L. Walston, Shohei Fujita, et al.
Diagnostic and Interventional Imaging (2024) Vol. 105, Iss. 11, pp. 453-459
Open Access | Times Cited: 16
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study
Simon Nusinovici, Tyler Hyungtaek Rim, Hengtong Li, et al.
The Lancet Healthy Longevity (2024), pp. 100593-100593
Open Access | Times Cited: 8
Simon Nusinovici, Tyler Hyungtaek Rim, Hengtong Li, et al.
The Lancet Healthy Longevity (2024), pp. 100593-100593
Open Access | Times Cited: 8
Data set terminology of deep learning in medicine: a historical review and recommendation
Shannon L. Walston, Hiroshi Seki, Hirotaka Takita, et al.
Japanese Journal of Radiology (2024) Vol. 42, Iss. 10, pp. 1100-1109
Closed Access | Times Cited: 6
Shannon L. Walston, Hiroshi Seki, Hirotaka Takita, et al.
Japanese Journal of Radiology (2024) Vol. 42, Iss. 10, pp. 1100-1109
Closed Access | Times Cited: 6
Recent trends in scientific research in chest radiology: What to do or not to do? That is the critical question in research
Hiroto Hatabu, Masahiro Yanagawa, Yoshitake Yamada, et al.
Japanese Journal of Radiology (2025)
Open Access
Hiroto Hatabu, Masahiro Yanagawa, Yoshitake Yamada, et al.
Japanese Journal of Radiology (2025)
Open Access
Artificial Intelligence Combined With Chest Radiography: New Hope for the Opportunistic Screening for Osteoporosis
Hongnan Ye
Korean Journal of Radiology (2025) Vol. 26
Closed Access
Hongnan Ye
Korean Journal of Radiology (2025) Vol. 26
Closed Access
External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs
Jong Hyuk Lee, Dongheon Lee, Michael T. Lu, et al.
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 5
Open Access | Times Cited: 2
Jong Hyuk Lee, Dongheon Lee, Michael T. Lu, et al.
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 5
Open Access | Times Cited: 2
Prostate Age Gap: An MRI Surrogate Marker of Aging for Prostate Cancer Detection
Álvaro Fernández-Quilez, Tobias Nordström, Fredrik Jäderling, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 60, Iss. 2, pp. 458-468
Open Access | Times Cited: 4
Álvaro Fernández-Quilez, Tobias Nordström, Fredrik Jäderling, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 60, Iss. 2, pp. 458-468
Open Access | Times Cited: 4
Advancing Liver Disease Sarcopenia Prediction: A Chest- Radiograph–Based Model for Older Adults
Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
AI analysis of chest radiographs as a biomarker of biological age
Paul Babyn, Scott Adams
The Lancet Healthy Longevity (2023) Vol. 4, Iss. 9, pp. e446-e447
Closed Access | Times Cited: 3
Paul Babyn, Scott Adams
The Lancet Healthy Longevity (2023) Vol. 4, Iss. 9, pp. e446-e447
Closed Access | Times Cited: 3
Chest Radiographs as Biological Clocks: Implications for Risk Stratification and Personalized Care
Lisa C. Adams, Keno K. Bressem
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 5
Open Access
Lisa C. Adams, Keno K. Bressem
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 5
Open Access
Deep learning to predict long-term mortality from plain chest X-ray in patients referred for suspected coronary artery disease
Giuseppe D'Ancona, Mattia Savardi, Mauro Massussi, et al.
Journal of Thoracic Disease (2024) Vol. 16, Iss. 8, pp. 4914-4923
Open Access
Giuseppe D'Ancona, Mattia Savardi, Mauro Massussi, et al.
Journal of Thoracic Disease (2024) Vol. 16, Iss. 8, pp. 4914-4923
Open Access
Application of artificial intelligence in thoracic radiology: A narrative review (Application of AI in thoracic radiology)
Woo Hyeon Lim, Hyungjin Kim
Tuberculosis & respiratory diseases (2024)
Open Access
Woo Hyeon Lim, Hyungjin Kim
Tuberculosis & respiratory diseases (2024)
Open Access
