Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers

Cited by (1,001)

Items 201–300 of 1,001

1. Evaluating ChatGPT-4V in chest CT diagnostics: a critical image interpretation assessment
   Reza Dehdab, Andreas Brendlin, Sebastian Werner, Haidara Almansour, Sebastian Gassenmaier, Jan Michael Brendel, Konstantin Nikolaou, Saif Afat · 2024 · Japanese Journal of Radiology
2. A deep learning model to enhance the classification of primary bone tumors based on incomplete multimodal images in X-ray, CT, and MRI
   Liwen Song, Chuanpu Li, Tan Lilian, Menghong Wang, Xiaqing Chen, Qiang Ye, Shisi Li, Rui Zhang, Qinghai Zeng, Zhuoyao Xie et al. · 2024 · Cancer Imaging
3. Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models
   Yasemin Küçükçiloğlu, Boran Şekeroğlu, Terin Adalı, Niyazi Şentürk · 2023 · Diagnostic and Interventional Radiology
4. Artificial intelligence in the autonomous navigation of endovascular interventions: a systematic review
   Harry H. Robertshaw, Lennart Karstensen, Benjamin M. Jackson, S. M. Hadi Sadati, Kawal Rhode, Sebastien Ourselin A, Alejandro Granados, Thomas Calvert Booth · 2023 · Frontiers in Human Neuroscience
5. An integrated model incorporating deep learning, hand-crafted radiomics and clinical and US features to diagnose central lymph node metastasis in patients with papillary thyroid cancer
   Yang Gao, Weizhen Wang, Yuan Yang, Ziting Xu, Yue Lin, Ting Lang, Shangtong Lei, Yisheng Xiao, Wei Yang, Weijun Huang et al. · 2024 · BMC Cancer
6. Artificial intelligence for MRI stroke detection: a systematic review and meta-analysis
   Jonas Asgaard Bojsen, Mohammad Talal Elhakim, Ole Graumann, David Gaist, Mads Nielsen, Frederik Severin Gråe Harbo, Christian Hedeager Krag, Malini Vendela Sagar, Christina Rostrup Kruuse, Mikael Boesen et al. · 2024 · Insights into Imaging
7. Artificial intelligence in rheumatology research: what is it good for?
   José Miguel Sequí-Sabater, Diego Benavent · 2025 · RMD Open
8. Deep learning-based breast cancer diagnosis in breast MRI: systematic review and meta-analysis
   Kamarul Amin Abdullah, Sara Marziali, Muzna Nanaa, Lorena Escudero Sánchez, Nicholas Roy Payne, Fiona J. Gilbert · 2025 · European Radiology
9. Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting
   Morone, Giovanni, De Angelis, Luigi, Martino Cinnera, Alex, Carbonetti, Riccardo, Bisirri, Alessio, Ciancarelli, Irene, Iosa, Marco, Negrini, Stefano, Kiekens, Carlotte, Negrini, Francesco · 2025 · Frontiers in Digital Health
10. Artificial intelligence tool development: what clinicians need to know?
    Chew, Boon-How, Ngiam, Kee Yuan · 2025 · BMC Medicine
11. Tasks for artificial intelligence in prostate MRI
    Mason J. Belue, Barış Türkbey · 2022 · European Radiology Experimental
12. Fully automatic cardiac four chamber and great vessel segmentation on CT pulmonary angiography using deep learning
    Michael J. Sharkey, Jonathan Christopher Taylor, Samer Alabed, Krit Dwivedi, Kavita Karunasaagarar, Christopher Johns, Smitha Rajaram, Pankaj Garg, Dheyaa Alkhanfar, Peter Metherall et al. · 2022 · Frontiers in Cardiovascular Medicine
13. Artificial intelligence-based radiomics models in endometrial cancer: A systematic review
    Lise Lecointre, Jérémy Dana, Massimo Lodi, Cherif Youssef Akladios, B. Gallix · 2021 · European Journal of Surgical Oncology
14. Deep Learning-Based Natural Language Processing in Radiology: The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance
    Allard W. Olthof, Peter M. A. van Ooijen, Ludo Johannes Cornelissen · 2021 · Journal of Medical Systems
15. Radiomics and Machine Learning Can Differentiate Transient Osteoporosis from Avascular Necrosis of the Hip
    Michail E. Klontzas, Georgios C. Manikis, Katerina Nikiforaki, Evangelia E. Vassalou, Konstantinos Spanakis, Ioannis Stathis, George A. Kakkos, Νικόλας Ματθαίου, Aristeidis H. Zibis, Kostas Marias A et al. · 2021 · Diagnostics
16. A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point of Care: The PACS-AI Platform
    Pascal Thériault-Lauzier, Denis Corbin, Olivier Tastet, Élodie Labrecque Langlais, Bahareh Taji, Guson Kang, Aun‐Yeong Chong, Derek Y F So, An Tang, Judy Wawira Gichoya et al. · 2024 · Canadian Journal of Cardiology
17. Artificial Intelligence and Machine Learning for Cardiovascular Computed Tomography (CCT): A White Paper of the Society of Cardiovascular Computed Tomography (SCCT)
    Michelle Claire Williams, Jonathan Richard Weir-McCall, Lauren Anne Baldassarre, Carlo Nicola De Cecco, Andrew D. Choi, Damini Dey, Marc Richard Dweck, Ivana Išgum, Márton Kolossváry, Jonathon A. Leipsic et al. · 2024 · Journal of cardiovascular computed tomography
18. Better Reporting of Studies on Artificial Intelligence: CONSORT-AI and Beyond
    Falk Schwendicke, Joachim Krois · 2021 · Journal of Dental Research
19. Machine Learning Applications for Differentiation of Glioma from Brain Metastasis—A Systematic Review
    Leon Jekel, Waverly Rose Brim, Marc von Reppert, Lawrence H. Staib, Gabriel Cassinelli Petersen, Sara Merkaj, Harry E. Subramanian, Tal Zeevi, Seyedmehdi Payabvash, Khaled Bousabarah et al. · 2022 · Cancers
20. Clinician-informed XAI evaluation checklist with metrics (CLIX-M) for AI-powered clinical decision support systems
    Brankovic, Aida, Cook, David, Rahman, Jessica, Delaforce, Alana, Li, Jane, Magrabi, Farah, Cabitza, Federico, Coiera, Enrico, Bradford, DanaKai · 2025 · npj Digital Medicine
21. Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion
    Satoshi Otani, Yuki Himoto, Mizuho Nishio, Koji Fujimoto, Yusaku Moribata, Masahiro Yakami, Yasuhisa Kurata, Junzo Hamanishi, Akihiko Ueda, Sachiko Minamiguchi et al. · 2021 · Magnetic Resonance Imaging
22. Convolutional neural network performance compared to radiologists in detecting intracranial hemorrhage from brain computed tomography: A systematic review and meta-analysis
    Mia Daugaard Jørgensen, Ronald Antulov, Søren Hess, Simon Lysdahlgaard · 2021 · European Journal of Radiology
23. Value assessment of artificial intelligence in medical imaging: a scoping review
    Iben Fasterholdt, Mohammad Naghavi‐Behzad, Benjamin Schnack Rasmussen, Tue Kjølhede, Mette Maria Skjøth, Malene Grubbe Hildebrandt, Kristian Kidholm · 2022 · BMC Medical Imaging
24. Are current clinical studies on artificial intelligence-based medical devices comprehensive enough to support a full health technology assessment? A systematic review
    Line Farah, Julie Davaze‐Schneider, Tess Martin, Pierre Nguyen, Isabelle Borget, Nicolas Martelli · 2023 · Artificial Intelligence in Medicine
25. Survey of AI-driven techniques for ovarian cancer detection: state-of-the-art methods and open challenges
    Samridhi Singh, Malti Kumari Maurya, Nagendra Singh, Rajeev Kumar · 2024 · Network Modeling Analysis in Health Informatics and Bioinformatics
26. How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Report Card
    Niklas Kühl, Robin Hirt, Lucas Baier, Björn Schmitz, Gerhard Satzger · 2021 · Communications of the Association for Information Systems
27. The Role of Radiomics in Lung Cancer: From Screening to Treatment and Follow-Up
    Radouane El Ayachy, Nicolas Giraud, Paul Giraud, Catherine Durdux, Philippe Giraud, Anita Burgun, Jean‐Emmanuel Bibault · 2021 · Frontiers in Oncology
28. Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis
    Burak Berksu Ozkara, Melissa Chen, Christian Federau, Mert Karabacak, Tina Marie Briere, Jing Li, Max Wintermark · 2023 · Cancers
29. Empirical Study on Classifiers for Earlier Prediction of COVID-19 Infection Cure and Death Rate in the Indian States
    Pratiyush Guleria, Shakeel Ahmed, Abdulaziz Alhumam, Parvathaneni Naga Srinivasu · 2022 · Healthcare
30. Automatic dental biofilm detection based on deep learning
    Katia MONTANHA-ANDRADE, Bernardo Peters Menezes Silva, Luciano Rebouças de Oliveira, Patrícia Ramos Cury · 2023 · Journal Of Clinical Periodontology
31. PET imaging of gliomas: Status quo and quo vadis?
    Norbert Galldiks, Philipp Lohmann, Michel Friedrich, Jan‐Michael Werner, Isabelle Stetter, Michael Wollring, Garry S. Ceccon, Carina Stegmayr, Sandra Krause, Gereon R. Fink et al. · 2024 · Neuro-Oncology
32. Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies
    Thomas Calvert Booth, Mariusz Tadeusz Grzeda, Alysha Chelliah, Andrei Roman, Ayisha Al Busaidi, Carmen Dragos, Haris Shuaib, Aysha Luis, Ayesha Mirchandani, Burcu Alparslan et al. · 2022 · Frontiers in Oncology
33. Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI)
    Iben Fasterholdt, Tue Kjølhede, Mohammad Naghavi‐Behzad, Thomas Schmidt, Quinnie T. S. Rautalammi, Malene Grubbe Hildebrandt, Anne Gerdes, Astrid Barkler, Kristian Kidholm, Valeria E. Rac et al. · 2022 · International Journal of Technology Assessment in Health Care
34. Deep learning in knee imaging: a systematic review utilizing a Checklist for Artificial Intelligence in Medical Imaging (CLAIM)
    Si, Liping, Zhong, Jingyu, Huo, Jiayu, Xuan, Kai, Zhuang, Zixu, Hu, Yangfan, Wang, Qian, Zhang, Huan, Yao, Weiwu · 2022 · European Radiology
35. An updated systematic review of radiomics in osteosarcoma: utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics
    Jingyu Zhong, Yangfan Hu, Guangcheng Zhang, Yue Xing, Defang Ding, Xiang Ge, Zhen Pan, Qingcheng Yang, Qian Yin, Huizhen Zhang et al. · 2022 · Insights into Imaging
36. Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT Examinations
    Bryan Dustin Pooler, John W. Garrett, A.M. Southard, Ronald M. Summers, Perry Joseph Pickhardt · 2023 · American Journal of Roentgenology
37. Automatic detection, segmentation, and classification of primary bone tumors and bone infections using an ensemble multi-task deep learning framework on multi-parametric MRIs: a multi-center study
    Qiang Ye, Hening Yang, Bomiao Lin, Menghong Wang, Liwen Song, Zhuoyao Xie, Zixiao Lu, Qianjin Feng, Yinghua Zhao · 2023 · European Radiology
38. Addressing hidden risks: Systematic review of artificial intelligence biases across racial and ethnic groups in cardiovascular diseases
    Riccardo Cau, Francesco Pisu, Jasjit S. Suri, Luca Saba · 2024 · European Journal of Radiology
39. Semantic segmentation of multispectral photoacoustic images using deep learning
    Melanie Schellenberg, Kris K. Dreher, Niklas Holzwarth, Fabian Isensee, Annika Reinke, Nicholas Schreck, Alexander Seitel, Minu D. Tizabi, Lena Maier‐Hein, Janek Gröhl · 2022 · Photoacoustics
40. Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review
    Andrés Mosquera‐Zamudio, Laëtitia Launet, Zahra Tabatabaei, Rafael Santiago Parra-Medina, Adrián Colomer, Javier Oliver Moll, Carlos Couceiro Monteagudo, Emiel A. M. Janssen, Valery Naranjo · 2022 · Cancers
41. The unintended consequences of artificial intelligence in paediatric radiology
    Pierluigi Ciet, Christine Eade, Mai‐Lan Ho, Lene Bjerke Laborie, Nasreen Mahomed, Jaishree Naidoo, Erika Pace, Bradley Segal, Seema Toso, Sebastian Tschauner et al. · 2023 · Pediatric Radiology
42. Artificial Intelligence for Detection of External Cervical Resorption Using Label-Efficient Self-Supervised Learning Method
    Hossein Mohammad‐Rahimi, Omid Dianat, Reza Abbasi, Samira Zahedrozegar, Ali Ashkan, Saeed Reza Motamedian, Mohammad Hossein Rohban, Ali Nosrat · 2023 · Journal of Endodontics
43. AI for Detection of Tuberculosis: Implications for Global Health
    Eui Jin Hwang, Won Gi Jeong, Pierre‐Marie David, Matthew Arentz, Morten Rühwald, Soon Ho Yoon · 2024 · Radiology Artificial Intelligence
44. Noninvasive Molecular Subtyping of Pediatric Low-Grade Glioma with Self-Supervised Transfer Learning
    Divyanshu Tak, Zezhong Ye, Anna Zapaishchykova, Yining Zha, Aidan Boyd, Sridhar Vajapeyam, Rishi Chopra, Hasaan Hayat, Sanjay P. Prabhu, Kevin X. Liu et al. · 2024 · Radiology Artificial Intelligence
45. The role of explainability in AI-supported medical decision-making
    Anne Gerdes · 2024 · Discover Artificial Intelligence
46. MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer
    Jing Ren, Yuan Li, Junjun Yang, Jia Wei Zhao, Yang Xiang, Xia Chen, Ying Cao, Bo Chen, Hui Guan, Yafei Qi et al. · 2022 · Insights into Imaging
47. Segmentation of Dental Restorations on Panoramic Radiographs Using Deep Learning
    Csaba Rohrer, Joachim Krois, Jay Sureshbhai Patel, Hendrik Meyer‐Lueckel, Jonas Almeida Rodrigues, Falk Schwendicke · 2022 · Diagnostics
48. Interpretable machine learning for prediction of clinical outcomes in acute ischemic stroke
    Joonwon Lee, Kang Min Park, Seong-Ho Park · 2023 · Frontiers in Neurology
49. Performance of GPT-4 on the American College of Radiology In-training Examination: Evaluating Accuracy, Model Drift, and Fine-tuning
    David L. Payne, Kush Purohit, Walter Morales Borrero, Katherine Chung, Max Hao, Mutshipay Mpoy, Michael X. Jin, Prateek Prasanna, Virginia B. Hill · 2024 · Academic Radiology
50. Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review
    Kareem A. Wahid, Zaphanlene Y. Kaffey, David P. Farris, Laia Humbert‐Vidan, Amy Catherine Moreno, Mathis Ersted Rasmussen, Jintao Ren, Mohamed A. Naser, Tucker Netherton, Stine Korreman et al. · 2024 · Radiotherapy and Oncology
51. Evaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis
    Nathaniel Barry, Jake Kendrick, Kaylee Molin, Suning Li, Pejman Rowshanfarzad, Ghulam Mubashar Hassan, Jason Dowling, Paul Maria Parizel, Michael S. Hofman, Martin A. Ebert · 2025 · European Radiology
52. Assessment of the Diagnostic Accuracy of Artificial Intelligence Software in Identifying Common Periodontal and Restorative Dental Conditions (Marginal Bone Loss, Periapical Lesion, Crown, Restoration, Dental Caries) in Intraoral Periapical Radiographs
    Wael Ibraheem, Saurabh Jain, Mohammed Ayoub, Mohammed Ahmed Namazi, Amjad Ismail Alfaqih, Aparna Aggarwal, Abdullah Ahmed Meshni, Ammar A. Almarghlani, Abdulkareem Abdullah Alhumaidan · 2025 · Diagnostics
53. Accelerating ophthalmic artificial intelligence research: the role of an open access data repository
    Ashley Kras, Leo Anthony Celi, John B. Miller · 2020 · Current Opinion in Ophthalmology
54. In-Series U-Net Network to 3D Tumor Image Reconstruction for Liver Hepatocellular Carcinoma Recognition
    Wen‐Fan Chen, Hsin‐You Ou, Keng-Hao Liu, Zhiyun Li, Chien-Chang Liao, Shaoyu Wang, Wen Huang, Yu‐Fan Cheng, Cheng‐Tang Pan · 2020 · Diagnostics
55. Generalizability of Deep Learning Models for Caries Detection in Near-Infrared Light Transillumination Images
    Agnes Holtkamp, Karim Elhennawy, José Eduardo Cejudo Grano de Oro, Joachim Krois, Sebastian Paris, Falk Schwendicke · 2021 · Journal of Clinical Medicine
56. Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT
    Mark Allen Christopher, Christopher Bowd, James A. Proudfoot, Akram Belghith, Michael H. Goldbaum, Jasmin Rezapour, Massimo A. Fazio, Christopher A. Girkin, Gustavo De Moraes, Jeffrey M. Liebmann et al. · 2021 · Ophthalmology
57. Artificial intelligence-based detection of aortic stenosis from chest radiographs
    Daiju Ueda, Akira Yamamoto, Shoichi Ehara, Shinichi Iwata, Koji Abo, Shannon Leigh Walston, Toshimasa Matsumoto, Akitoshi Shimazaki, Minoru Yoshiyama, Yukio Miki · 2021 · European Heart Journal - Digital Health
58. How Can We Ensure Reproducibility and Clinical Translation of Machine Learning Applications in Laboratory Medicine?
    Shannon Haymond, Stephen R. Master · 2021 · Clinical Chemistry
59. Artificial Intelligence in Clinical Practice: Implementation Considerations and Barriers
    Manisha Bahl · 2022 · Journal of Breast Imaging
60. Implementation of artificial intelligence in thoracic imaging—a what, how, and why guide from the European Society of Thoracic Imaging (ESTI)
    Fergus Vincent Gleeson, Marie‐Pierre Revel, Jürgen Biederer, Anna Rita Larici, Katharina Martini, Thomas Frauenfelder, Nicholas John Screaton, Helmut Prosch, Annemiek Snoeckx, Nicola Sverzellati et al. · 2023 · European Radiology
61. Using preregistration as a tool for transparent fNIRS study design
    Philipp Alexander Schroeder, Christina Artemenko, Jessica Elizabeth Kosie, Helena Cockx, Katharina Stute, João Pereira, Franziska Klein, David M. A. Mehler · 2023 · Neurophotonics
62. Radiomics for the identification of extraprostatic extension with prostate MRI: a systematic review and meta-analysis
    Andrea Ponsiglione, Michele Gambardella, Arnaldo Stanzione, Roberta Green, Valeria Cantoni, Carmela Nappi, Felice Crocetto, Renato Cuocolo, Alberto Cuocolo, Massimo Imbriaco · 2023 · European Radiology
63. Core outcomes measures in dental computer vision studies (DentalCOMS)
    Martha Büttner, Rata Rokhshad, Janet Brinz, Julien Issa, Akhilanand Chaurasia, Sergio E. Uribe, Teodora Karteva, Sanaa Chala, Antonín Tichý, Falk Schwendicke · 2024 · Journal of Dentistry
64. Artificial Intelligence and Radiomics in Head and Neck Cancer Care: Opportunities, Mechanics, and Challenges
    Lisanne Vania van Dijk, Clifton David Fuller · 2021 · American Society of Clinical Oncology Educational Book
65. Synthetic FLAIR as a Substitute for FLAIR Sequence in Acute Ischemic Stroke
    Joseph Benzakoun, Marc-Antoine Deslys, Laurence Legrand, Ghazi Hmeydia, Guillaume Turc, Wagih Ben Hassen, Sylvain Charron, Clément Debacker, Olivier N. Naggara, Jean‐Claude Baron et al. · 2022 · Radiology
66. Tensor-RT-Based Transfer Learning Model for Lung Cancer Classification
    Vidhi Bishnoi, Nidhi Goel · 2023 · Journal of Imaging Informatics in Medicine
67. Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review
    Mana Moassefi, Pouria Rouzrokh, Gian Marco Conte, Sanaz Vahdati, Tianyuan Fu, Aylin Tahmasebi, Mira Younis, Keyvan Farahani, Amilcare Gentili, Timothy Lee Kline et al. · 2023 · Journal of Imaging Informatics in Medicine
68. Comparative Analysis of Diabetic Retinopathy Classification Approaches Using Machine Learning and Deep Learning Techniques
    Ruchika Bala, Arun Sharma, Nidhi Goel · 2023 · Archives of Computational Methods in Engineering
69. Machine Learning-Based Breast Tumor Ultrasound Radiomics for Pre-operative Prediction of Axillary Sentinel Lymph Node Metastasis Burden in Early-Stage Invasive Breast Cancer
    Jiejie Yao, Wei Zhou, Shangyan Xu, Xiaohong Jia, Jianqiao Zhou, Xiaosong Chen, Weiwei Zhan · 2023 · Ultrasound in Medicine & Biology
70. Generative adversarial networks in dental imaging: a systematic review
    Sujin Yang, Kee‐Deog Kim, Eiichiro Ariji, Yoshitaka Kise · 2023 · Oral Radiology
71. Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation
    Tingwei Wang, Jia‐Sheng Hong, Jing-Wen Huang, Chien-Yi Liao, Chia‐Feng Lu, Yu‐Te Wu · 2024 · Radiotherapy and Oncology
72. Evaluation of Advanced Artificial Intelligence Algorithms’ Diagnostic Efficacy in Acute Ischemic Stroke: A Comparative Analysis of ChatGPT-4o and Claude 3.5 Sonnet Models
    Mustafa Koyun, İsmail Taşkent · 2025 · Journal of Clinical Medicine
73. Artificial intelligence for diagnosis of fractures on plain radiographs: A scoping review of current literature
    Clare Rainey, Jonathan McConnell, Ciara Hughes, Raymond Bond, Sonyia L. McFadden · 2021 · Intelligence-Based Medicine
74. Automated brain tumor identification using magnetic resonance imaging: A systematic review and meta-analysis
    Omar Kouli, Ahmed S. I. Hassane, Dania Badran, Tasnim Kouli, Kismet Hossain-Ibrahim, J. Douglas Steele · 2022 · Neuro-Oncology Advances
75. Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability
    Britt B. S. L. Houwen, Karlijn J. Nass, Jasper L.A. Vleugels, Paul Fockens, Yark Hazewinkel, Evelien Dekker · 2022 · Gastrointestinal Endoscopy
76. Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels
    Pyeong Hwa Kim, Hee Mang Yoon, Jeong Rye Kim, Jae‐Yeon Hwang, Jin‐Ho Choi, Jisun Hwang, Jae-Won Lee, Jinkyeong Sung, Kyu-Hwan Jung, Byeonguk Bae et al. · 2023 · Korean Journal of Radiology
77. Untitled work
    2024 · 10.1038/s42256-023-00717-2
78. Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study
    Venkatesh, Kesavan, Santomartino, Samantha M., Sulam, Jeremias, Yi, Paul H. · 2022 · Radiology: Artificial Intelligence
79. Randomized Controlled Trials in Medical AI
    Konstantin Genin, Thomas Grote · 2021 · Philosophy of Medicine
80. Comparative performances of machine learning algorithms in radiomics and impacting factors
    Antoine Decoux, Loïc Duron, Paul Habert, Victoire Roblot, Emina Arsovic, Guillaume Chassagnon, Armelle Arnoux, Laure S Fournier · 2023 · Scientific Reports
81. Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis
    Soroush Sadr, Rata Rokhshad, Yasaman Daghighi, Mohsen Golkar, Fateme Tolooie Kheybari, Fatemeh Gorjinejad, Atousa Mataji Kojori, Parisa Rahimirad, Parnian Shobeiri, Mina Mahdian et al. · 2023 · Dentomaxillofacial Radiology
82. Glioblastoma and radiotherapy: A multicenter AI study for Survival Predictions from MRI (GRASP study)
    Alysha Chelliah, David A. Wood, Liane S. Canas, Haris Shuaib, Stuart Currie, Kavi Fatania, Russell Thomas Frood, Chris Rowland-Hill, Stefanie Catherine Thust, Stephen J. Wastling et al. · 2024 · Neuro-Oncology
83. Large Language Models in radiology: A technical and clinical perspective
    Jyun-Ping Kao, Huan-Tang Kao · 2025 · European Journal of Radiology Artificial Intelligence
84. Knowledge and attitudes towards artificial intelligence in imaging: a look at the quantitative survey literature
    Abhishta Bhandari, Sai Navya Purchuri, Chinmay Sharma, Muhammad Ibrahim, Marita Prior · 2021 · Clinical Imaging
85. Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce
    C. Parkinson, C. Matthams, Kieran Foley, Emiliano Spezi · 2021 · Radiography
86. Deep Learning-Based Computer-Aided Detection System for Automated Treatment Response Assessment of Brain Metastases on 3D MRI
    Cho, Jungheum, Kim, Young Jae, Sunwoo, Leonard, Lee, Gi Pyo, Nguyen, Toan Quang, Cho, Se Jin, Baik, Sung Hyun, Bae, Yun Jung, Choi, Byung Se, Jung, Cheolkyu et al. · 2021 · Frontiers in Oncology
87. Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework
    Brady J. Williamson, Vivek J. Khandwala, David Wang, Thomas Maloney, Heidi J. Sucharew, Paul S. Horn, Mary A. Haverbusch, Kathleen Alwell, Shantala Gangatirkar, Abdelkader Mahammedi et al. · 2022 · Scientific Reports
88. MRI ‐Based Artificial Intelligence in Rectal Cancer
    Chinting Wong, Yu Fu, Mingyang Li, Shengnan Mu, Xiaotong Chu, Jiahui Fu, Chenghe Lin, Huimao Zhang · 2022 · Journal of Magnetic Resonance Imaging
89. A deep learning model for prognosis prediction after intracranial hemorrhage
    Amaia Pérez del Barrio, Anna Esteve Domínguez, Pablo Menéndez Fernández‐Miranda, Pablo Sanz Bellón, David Rodriguez, L. Lloret Iglesias, Enrique Marqués Fraguela, Andrés A. González Mandly, José A. Vega · 2022 · Journal of Neuroimaging
90. Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for Amplifying the Signal While Reducing the Noise
    Derek Driggs, IAN A. SELBY, Michael T. Roberts, Effrossyni Gkrania‐Klotsas, James H F Rudd, Guang Yang, Judith L Babar, Evis Sala, Carola‐Bibiane Schönlieb · 2021 · Radiology Artificial Intelligence
91. An Endodontic Forecasting Model Based on the Analysis of Preoperative Dental Radiographs: A Pilot Study on an Endodontic Predictive Deep Neural Network
    Junghoon Lee, Hyunseok Seo, Yoon Jeong Choi, Chena Lee, Sunil Kim, Ye Sel Lee, Sukjoon Lee, Euiseong Kim · 2023 · Journal of Endodontics
92. Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging
    Krunoslav Michael Sveric, Stefan Ulbrich, Zouhir Dindane, Anna Winkler, Roxana Botan, Johannes Mierke, Anne Trausch, Felix Matthias Heidrich, Axel Hans-Peter Linke · 2023 · International Journal of Cardiology
93. ESMO Guidance for Reporting Oncology real-World evidence (GROW)
    Luís Castelo-Branco, Anna Pellat, Diogo Alexandre Martins-Branco, Antonios Valachis, Jeroen W. G. Derksen, Karijn P.M. Suijkerbuijk, Urania G. Dafni, Tereza Dellaporta, Arndt Vogel, Arsela Prelaj et al. · 2023 · ESMO Real World Data and Digital Oncology
94. AI‐Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI : Traversing the Landscape of Conventional to Explainable Approaches
    Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri · 2024 · Journal of Magnetic Resonance Imaging
95. Robustness and reproducibility for AI learning in biomedical sciences: RENOIR
    Alessandro Barberis, Hugo J.W.L. Aerts, Francesca Meteora Buffa · 2024 · Scientific Reports
96. Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology
    Allison Chae, Michael S. Yao, Hersh Sagreiya, Ari D. Goldberg, Neil R. Chatterjee, Matthew T. MacLean, Jeffrey Duda, Ameena Elahi, Arijitt Borthakur, Marylyn DeRiggi Ritchie et al. · 2024 · Radiology
97. X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones
    Salvatore Gitto, Alessio Annovazzi, Kitija Nulle, Matteo Interlenghi, Christian Salvatore, Vincenzo Anelli, Jacopo Baldi, Carmelo Messina, Domenico Albano, Filippo Di Luca et al. · 2024 · EBioMedicine
98. Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning
    Constantin Anastasopoulos, Thomas Weikert, Shan Yang, Ahmed Abdulkadir, Lena Schmülling, Claudia Bühler, Fabiano Paciolla, Raphael Sexauer, Joshy Cyriac, Ivan Nešić et al. · 2020 · European Journal of Radiology
99. A deep learning algorithm for white matter hyperintensity lesion detection and segmentation
    Yajing Zhang, Yunyun Duan, Xiaoyang Wang, Zhizheng Zhuo, Sven Haller, Frederik Barkhof, Yaou Liu · 2021 · Neuroradiology
100. Comparative Performance of Deep Learning and Radiologists for the Diagnosis and Localization of Clinically Significant Prostate Cancer at MRI: A Systematic Review
     Christian Roest, Stefan Johannes Fransen, Thomas Christian Kwee, Derya Yakar · 2022 · Life