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:

Current applications and future directions of deep learning in musculoskeletal radiology
Pauley Chea, Jacob Mandell
Skeletal Radiology (2019) Vol. 49, Iss. 2, pp. 183-197
Closed Access | Times Cited: 110

Showing 1-25 of 110 citing articles:

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi, Jinglan Zhang, Amjad J. Humaidi, et al.
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 4827
Automated detection of COVID-19 using ensemble of transfer learning with deep convolutional neural network based on CT scans
Parisa Gifani, Ahmad Shalbaf, Majid Vafaeezadeh
International Journal of Computer Assisted Radiology and Surgery (2020) Vol. 16, Iss. 1, pp. 115-123
Open Access | Times Cited: 161
Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions
Shahnawaz Ahmad, Iman Shakeel, Shabana Mehfuz, et al.
Computer Science Review (2023) Vol. 49, pp. 100568-100568
Closed Access | Times Cited: 76
Analysis and Prediction of Students’ Academic Performance Based on Educational Data Mining
Guiyun Feng, Muwei Fan, Yu Chen
IEEE Access (2022) Vol. 10, pp. 19558-19571
Open Access | Times Cited: 71
How AI May Transform Musculoskeletal Imaging
Ali Guermazi, Patrick Omoumi, Mickaël Tordjman, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 17
Diagnosing osteoarthritis from T2 maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort
Valentina Pedoia, Jinwoo Lee, Berk Norman, et al.
Osteoarthritis and Cartilage (2019) Vol. 27, Iss. 7, pp. 1002-1010
Open Access | Times Cited: 91
A scalable physician-level deep learning algorithm detects universal trauma on pelvic radiographs
Chi‐Tung Cheng, Yirui Wang, Huan‐Wu Chen, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 72
Artificial Intelligence in Emergency Radiology: Where Are We Going?
Michaela Cellina, Maurizio Cè, Giovanni Irmici, et al.
Diagnostics (2022) Vol. 12, Iss. 12, pp. 3223-3223
Open Access | Times Cited: 39
Deep Learning Diagnosis and Classification of Rotator Cuff Tears on Shoulder MRI
Dana J. Lin, Michael Schwier, Bernhard Geiger, et al.
Investigative Radiology (2023) Vol. 58, Iss. 6, pp. 405-412
Closed Access | Times Cited: 26
ChatGPT’s diagnostic performance based on textual vs. visual information compared to radiologists’ diagnostic performance in musculoskeletal radiology
Daisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, et al.
European Radiology (2024) Vol. 35, Iss. 1, pp. 506-516
Open Access | Times Cited: 15
Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis
Akshay Chaudhari, Feliks Kogan, Valentina Pedoia, et al.
Journal of Magnetic Resonance Imaging (2019) Vol. 52, Iss. 5, pp. 1321-1339
Open Access | Times Cited: 57
HFRU-Net: High-Level Feature Fusion and Recalibration UNet for Automatic Liver and Tumor Segmentation in CT Images
Devidas T. Kushnure, Sanjay N. Talbar
Computer Methods and Programs in Biomedicine (2021) Vol. 213, pp. 106501-106501
Closed Access | Times Cited: 50
Artificial intelligence, machine learning and deep learning in musculoskeletal imaging: Current applications
Tommaso D’Angelo, Danilo Caudo, Alfredo Blandino, et al.
Journal of Clinical Ultrasound (2022) Vol. 50, Iss. 9, pp. 1414-1431
Closed Access | Times Cited: 36
Deep Learning-Assisted Diagnosis of Pediatric Skull Fractures on Plain Radiographs
Jae Won Choi, Yeon Jin Cho, Ji Young Ha, et al.
Korean Journal of Radiology (2022) Vol. 23, Iss. 3, pp. 343-343
Open Access | Times Cited: 31
Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI
Jason Yao, Leonid Chepelev, Yashmin Nisha, et al.
Skeletal Radiology (2022) Vol. 51, Iss. 9, pp. 1765-1775
Closed Access | Times Cited: 29
Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol
Carl Petter Skaar Kulseng, Varatharajan Nainamalai, Endre Grøvik, et al.
BMC Musculoskeletal Disorders (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 21
Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms
V. Bousson, Grégoire Attané, Nicolas Benoist, et al.
Academic Radiology (2023) Vol. 30, Iss. 10, pp. 2118-2139
Open Access | Times Cited: 18
Rapid lumbar MRI protocol using 3D imaging and deep learning reconstruction
J. Levi Chazen, Ek T. Tan, Jake Fiore, et al.
Skeletal Radiology (2023) Vol. 52, Iss. 7, pp. 1331-1338
Closed Access | Times Cited: 17
Artificial Intelligence in Radiology
Muhammad Rehan Khan
Elsevier eBooks (2024), pp. 149-177
Closed Access | Times Cited: 7
Automated detection and classification of shoulder arthroplasty models using deep learning
Paul H. Yi, Tae Kyung Kim, Jinchi Wei, et al.
Skeletal Radiology (2020) Vol. 49, Iss. 10, pp. 1623-1632
Closed Access | Times Cited: 47
Artificial intelligence in paediatric radiology: Future opportunities
Natasha Davendralingam, Neil J. Sebire, Owen J. Arthurs, et al.
British Journal of Radiology (2020) Vol. 94, Iss. 1117
Open Access | Times Cited: 43
Artificial intelligence in musculoskeletal imaging: a perspective on value propositions, clinical use, and obstacles
Jan Fritz, Richard Kijowski, Michael P. Recht
Skeletal Radiology (2021) Vol. 51, Iss. 2, pp. 239-243
Closed Access | Times Cited: 35
A deep learning–machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors
Renyi Liu, Derun Pan, Yuan Xu, et al.
European Radiology (2021) Vol. 32, Iss. 2, pp. 1371-1383
Closed Access | Times Cited: 35
Deep learning applications in osteoarthritis imaging
Richard Kijowski, Jan Fritz, Cem M. Deniz
Skeletal Radiology (2023) Vol. 52, Iss. 11, pp. 2225-2238
Open Access | Times Cited: 16
The promise and limitations of artificial intelligence in musculoskeletal imaging
Patrick Debs, Laura M. Fayad
Frontiers in Radiology (2023) Vol. 3
Open Access | Times Cited: 15
Page 1 - Next Page

Scroll to top