Checklist for Artificial Intelligence in Medical Imaging (CLAIM): a guide for authors and reviewers

Cited by (1,001)

Items 401–500 of 1,001

1. Assessment of artificial intelligence (AI) reporting methodology in glioma MRI studies using the Checklist for AI in Medical Imaging (CLAIM)
   Bhandari, Abhishta, Scott, Luke, Weilbach, Manuela, Marwah, Ravi, Lasocki, Arian · 2023 · Neuroradiology
2. Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence
   Kenta Horita, Koya Hida, Yoshiro Itatani, Haruku Fujita, Yu Hidaka, Goshiro Yamamoto, Masaaki Ito, Kazutaka Obama · 2024 · Surgical Endoscopy
3. Artificial intelligence (AI) in radiological paediatric fracture assessment: an updated systematic review
   Emily Ashworth, Emma Allan, Cato Pauling, Harsimran Laidlow-Singh, Owen John Arthurs, Susan Cheng Shelmerdine · 2025 · European Radiology
4. Artificial Intelligence in Detecting Periodontal Disease From Intraoral Photographs: A Systematic Review
   Kaijing Mao, Khaing Myat Thu, Kuo Feng Hung, Ollie Yiru Yu, Tai-Chiu Hsung, Walter Yu Hang Lam · 2025 · International Dental Journal
5. Automatic segmentation of prostate zonal anatomy on MRI: a systematic review of the literature
   Carine Wu, Sarah Montagne, Dimitri Hamzaoui, Nicholas Ayache, Hervé Delingette, Raphaële Renard‐Penna · 2022 · Insights into Imaging
6. Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides
   Luca Cerny Oliveira, Zhengfeng Lai, Danielle Jenine Harvey, Kevin Nzenkue, Lee‐Way Jin, Charles S DeCarli, Chen‐Nee Chuah, Brittany N. Dugger · 2023 · Journal of Neuropathology & Experimental Neurology
7. Position statement on clinical evaluation of imaging AI
   Cathal McCague, Katherine Mackay, Ceilidh Welsh, Alex Constantinou, Rajesh Jena, Mireia Crispin‐Ortuzar, Cathal McCague, Katherine Mackay, Ceilidh Welsh, Alex Constantinou et al. · 2023 · The Lancet Digital Health
8. Radiologist’s Guide to Evaluating Publications of Clinical Research on AI: How We Do It
   Seong Ho Park, Ah-Ram Sul, Yousun Ko, Hye Young Jang, June‐Goo Lee · 2023 · Radiology
9. Prediction of cerebral hemorrhagic transformation after thrombectomy using a deep learning of dual-energy CT
   JoonNyung Heo, Youngno Yoon, Hyun Jin Han, Jung‐Jae Kim, Keun Young Park, Byung Moon Kim, Dong Joon Kim, Young Dae Kim, Hyo Suk Nam, Seung‐Koo Lee et al. · 2023 · European Radiology
10. Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: a retrospective, multicentre study
    Jingjing You, Yue Ming Huang, Lizhu Ouyang, Xiao Zhang, Pei‐Jer Chen, Xuewei Wu, Zhe Jin, Hui Shen, Lu Zhang, Qiuying Chen et al. · 2024 · EClinicalMedicine
11. End-to-end reproducible AI pipelines in radiology using the cloud
    Dennis Bontempi, Leonard Nürnberg, Suraj Pai, Deepa Krishnaswamy, Vamsi Thiriveedhi, Ahmed Hosny, Raymond H. Mak, Keyvan Farahani, Ron Kikinis, Andriy Fedorov et al. · 2024 · Nature Communications
12. Application of a deep learning algorithm for the diagnosis of HCC
    Philip L. H. Yu, Keith Wan-Hang Chiu, Jianliang Lu, Gilbert C.S. Lui, Jian Zhou, Ho Ming Cheng, Xianhua Mao, Juan Wu, Xinping Shen, King Ming Kwok et al. · 2024 · JHEP Reports
13. Checklist for Reproducibility of Deep Learning in Medical Imaging
    Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile M. Safdar, Linda P. Moy, Felipe Kitamura, Amilcare Gentili et al. · 2024 · Journal of Imaging Informatics in Medicine
14. The Accuracy of ChatGPT-4o in Interpreting Chest and Abdominal X-Ray Images
    Pietro Giacomo Lacaita, Malik Galijašević, Michael Swoboda, Leonhard N. Gruber, Yannick Scharll, Fabian Barbieri, Gerlig Widmann, Gudrun Maria Feuchtner · 2025 · Journal of Personalized Medicine
15. Randomized Controlled Trials Evaluating Artificial Intelligence in Cardiovascular Care
    Dor Hadida Barzilai, Karin Sudri, Gal Goshen, Eyal Klang, Eyal Zimlichman, Israel Moshe Barbash, Michal Shelly Cohen · 2025 · JACC Advances
16. Artificial intelligence reporting guidelines: what the pediatric radiologist needs to know
    Riwa Meshaka, Daniel Pinto dos Santos, Owen John Arthurs, Neil James Sebire, Susan Cheng Shelmerdine · 2021 · Pediatric Radiology
17. Predictive values of AI-based triage model in suboptimal CT pulmonary angiography
    Shadi Ebrahimian, Subba Rao Digumarthy, Fatemeh Homayounieh, Bernardo Canedo Bizzo, Keith J. Dreyer, Mannudeep K. Kalra · 2022 · Clinical Imaging
18. Deep Learning for the Differential Diagnosis between Transient Osteoporosis and Avascular Necrosis of the Hip
    Michail E. Klontzas, Ioannis Stathis, Konstantinos Spanakis, Aristeidis H. Zibis, Kostas Marias A, Apostolos H. Karantanas · 2022 · Diagnostics
19. Performance variability of radiomics machine learning models for the detection of clinically significant prostate cancer in heterogeneous MRI datasets
    Eva Gresser, Balthasar Maria Schachtner, Anna Theresa Stüber, Olga Solyanik, Andrea Schreier, Thomas S. Huber, Matthias Frank Froelich, Giuseppe Magistro, Alexander Kretschmer, Christian Georg Stief et al. · 2022 · Quantitative Imaging in Medicine and Surgery
20. Artificial Intelligence for Outcome Modeling in Radiotherapy
    Sunan Cui, Andrew J. Hope, Thomas J. Dilling, Laura Ann Dawson, Randall K. Ten Haken, Issam El Naqa · 2022 · Seminars in Radiation Oncology
21. Reproducibility of artificial intelligence models in computed tomography of the head: a quantitative analysis
    Felix Gunzer, Michael Jantscher, Eva Maria Hassler, Thomas Kau, Gernot Reishofer · 2022 · Insights into Imaging
22. MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review
    Luis Fernando Calimano-Ramirez, Mayur Virarkar, Mauricio Hernandez, Savas Ozdemir, Sindhu P. Kumar, Dheeraj Reddy Gopireddy, Chandana G. Lall, K.C. Balaji, Mutlu Mete, Kazım Gümüş · 2023 · Abdominal Radiology
23. Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI
    Hyungseob Shin, Ji Eun Park, Yohan Jun, Taejoon Eo, Jeongryong Lee, Ji Eun Kim, Da Hyun Lee, Hye Hyeon Moon, Sang Ik Park, Seon‐Ok Kim et al. · 2023 · European Radiology
24. Complexities of deep learning-based undersampled MR image reconstruction
    Constant R. Noordman, Derya Yakar, Joeran S. Bosma, Frank F.J. Simonis, HenkJan J. Huisman · 2023 · European Radiology Experimental
25. The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study
    Jingyu Zhong, Yue Xing, Junjie Anderson Lu, Guangcheng Zhang, Shiqi Mao, Haoda Chen, Qian Yin, Qingqing Cen, Run Jiang, Yangfan Hu et al. · 2023 · BMC Medical Research Methodology
26. Prediction of treatment response after stereotactic radiosurgery of brain metastasis using deep learning and radiomics on longitudinal MRI data
    Se Jin Cho, Wonwoo Cho, Dongmin Choi, Gyuhyeon Sim, So Yeong Jeong, Sung Hyun Baik, Yun Jung Bae, Byung Se Choi, Jae Hyoung Kim, Sooyoung Yoo et al. · 2024 · Scientific Reports
27. Standalone deep learning versus experts for diagnosis lung cancer on chest computed tomography: a systematic review
    Tingwei Wang, Jia‐Sheng Hong, Hwa‐Yen Chiu, Heng‐Sheng Chao, Yuh‐Min Chen, Yu‐Te Wu · 2024 · European Radiology
28. Deep learning using computed tomography to identify high-risk patients for acute small bowel obstruction: development and validation of a prediction model : a retrospective cohort study
    Seungmin Oh, Jongbin Ryu, Ho-Jung Shin, Jeong Ho Song, Sang‐Yong Son, Hoon Hur, Sang‐Uk Han · 2023 · International Journal of Surgery
29. Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap!
    Ioanna Chouvarda, Sara Colantonio, Ana Sofia Castro Verde, Ana Jiménez-Pastor, Leonor Cerdá-Alberich, Yannick Metz, Lithin Zacharias, Shereen Nabhani‐Gebara, Maciej Bobowicz, Gianna Tsakou et al. · 2025 · European Radiology Experimental
30. Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy–Related Cardiovascular Toxicity: Systematic Review
    Hayat Mushcab, Mohammed Al Ramis, Abdulrahman Alrujaib, Rawan Eskandarani, Tamara Sunbul, Anwar Alotaibi, Mohammed Obaidan, Reman Alharbi, Duaa Aljabri · 2025 · JMIR Cancer
31. Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews
    Haishan Xu, Ting‐Ting Gong, Xin‐Jian Song, Qian Chen, Qi Bao, Wei Yao, Meng-Meng Xie, Chen Li, Marcin Grzegorzek, Yu Shi et al. · 2025 · Journal of Medical Internet Research
32. An MRI–pathology foundation model for noninvasive diagnosis and grading of prostate cancer
    Lizhi Shao, Chao Liang, Ye Yan, Haibin Zhu, Xiao‐Ming Jiang, Meiling Bao, Pan Zang, Xiazi Huang, Hongyu Zhou, Pei Nie et al. · 2025 · Nature Cancer
33. Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities
    Sara Merkaj, Ryan C. Bahar, Tal Zeevi, MingDe Lin, Ichiro Ikuta, Khaled Bousabarah, Gabriel Cassinelli Petersen, Lawrence H. Staib, Seyedmehdi Payabvash, John Mongan et al. · 2022 · Cancers
34. Quality assessment of machine learning models for diagnostic imaging in orthopaedics: A systematic review
    Amanda Lans, Robert‐Jan Pierik, John R. Bales, Mitchell Stephen Fourman, David Shin, Laura N. Kanbier, Jack Rifkin, William DiGiovanni, Rohan R. Chopra, Rana Moeinzad et al. · 2022 · Artificial Intelligence in Medicine
35. Beyond diagnosis: is there a role for radiomics in prostate cancer management?
    Arnaldo Stanzione, Andrea Ponsiglione, Francesco Alessandrino, Giorgio Brembilla, Massimo Imbriaco · 2023 · European Radiology Experimental
36. Artificial intelligence in neuroradiology: a scoping review of some ethical challenges
    Pegah Khosravi, Mark Schweitzer · 2023 · Frontiers in Radiology
37. The Evolution and Reliability of Machine Learning Techniques for Oncology
    Hamza Abu Owida, Bashar Al-haj Moh’d, Nidal M. Turab, Jamal Al-Nabulsi, Suhaila Farhan Ahmad Abuowaida · 2023 · International Journal of Online and Biomedical Engineering (iJOE)
38. Performance of a commercially available artificial intelligence software for the detection of confirmed pulmonary nodules and masses in canine thoracic radiography
    Leah Pomerantz, Mauricio Solano, Eric Kalosa‐Kenyon · 2023 · Veterinary Radiology & Ultrasound
39. Deep Learning Radiomics Nomogram Based on Magnetic Resonance Imaging for Differentiating Type I/II Epithelial Ovarian Cancer
    Mingxiang Wei, Guannan Feng, Xinyi Wang, Jianye Jia, Yu Zhang, Yao Dai, Cai Qin, Genji Bai, Shuangqing Chen · 2023 · Academic Radiology
40. Evaluating the performance of artificial intelligence software for lung nodule detection on chest radiographs in a retrospective real-world UK population
    Ahmed Maiter, Katherine Hocking, S. Matthews, Jonathan Christopher Taylor, Michael J. Sharkey, Peter Metherall, Samer Alabed, Krit Dwivedi, Yousef Shahin, Elizabeth Anderson et al. · 2023 · BMJ Open
41. An overview of clinical machine learning applications in neurology
    Colin M. Smith, Allison L. Weathers, Steven L. Lewis · 2023 · Journal of the Neurological Sciences
42. Vision Transformer–based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool
    Christopher W. Smith, Armaan Kush Malhotra, Christopher F. Hammill, Derek Beaton, Erin M. Harrington, Yingshi He, Husain Shakil, Amanda McFarlan, Blair Jones, Hui Ming Lin et al. · 2024 · Radiology Artificial Intelligence
43. Interpretable artificial intelligence-based app assists inexperienced radiologists in diagnosing biliary atresia from sonographic gallbladder images
    Wenying Zhou, Zejun Ye, Guangliang Huang, Xiaoer Zhang, Ming Tong Xu, Baoxian Liu, Bowen Zhuang, Zijian Tang, Shan Wang, Dan Chen et al. · 2024 · BMC Medicine
44. A systematic review of artificial intelligence tools for chronic pulmonary embolism on CT pulmonary angiography
    Lojain Abdulaal, Ahmed Maiter, Mahan Salehi, Michael J. Sharkey, Turki Nasser Alnasser, Pankaj Garg, Smitha Rajaram, Catherine Hill, Christopher Johns, Alexander M.K. Rothman et al. · 2024 · Frontiers in Radiology
45. Clinical Applications of Machine Learning
    Nadayca Mateussi, Michael P. Rogers, Emily A. Grimsley, Meagan D. Read, Rajavi Parikh, Ricardo S. Pietrobon, Paul C. Kuo · 2024 · Annals of Surgery Open
46. Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools
    Luca Russo, Silvia Bottazzi, Burak Koçak, Konstantinos Zormpas‐Petridis, Benedetta Gui, Arnaldo Stanzione, Massimo Imbriaco, Evis Sala, Renato Cuocolo, Andrea Ponsiglione · 2024 · European Radiology
47. Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review
    Negisa Seyyedi, Ali Ghafari, Navisa Seyyedi, Peyman Sheikhzadeh · 2024 · BMC Medical Imaging
48. Deep learning in medical image analysis: introduction to underlying principles and reviewer guide using diagnostic case studies in paediatrics
    Constance Dubois, David Eigen, Emmanuel Delmas, Margot Einfalt, Clara Lemaçon, Laureline Berteloot, Patrick M. Bossuyt, David Drummond, Pauline Scherdel, François Simon et al. · 2024 · BMJ
49. Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs
    Wan Hang Keith Chiu, Varut Vardhanabhuti, Dmytro Poplavskiy, Philip L. H. Yu, Richard Du, Alistair Yun Hee Yap, Sailong Zhang, Ambrose Ho-Tung Fong, Thomas Wing-Yan Chin, Jonan Chun Yin Lee et al. · 2020 · Journal of Thoracic Imaging
50. Evaluating Diagnostic Performance of ChatGPT in Radiology: Delving into Methods
    David K.B. Li, Kartik Gupta, Jaron Chong · 2023 · Radiology
51. Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM
    Kocak, Burak, Keles, Ali, Akinci D’Antonoli, Tugba · 2023 · European Radiology
52. Integrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography
    Yi Yang, Chang Zhao, Xin Nie, Jun Wu, Jingang Chen, W Liu, Hongwei He, Shuo Wang, Chengcheng Zhu, Qingyuan Liu · 2024 · Radiology Artificial Intelligence
53. Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis
    Branimir Rusanov, Martin A. Ebert, Mahsheed Sabet, Pejman Rowshanfarzad, Nathaniel Barry, Jake Kendrick, Zaid Alkhatib, Suki Gill, Joshua Dass, Nicholas W. Bucknell et al. · 2025 · Physical and Engineering Sciences in Medicine
54. Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis
    Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh · 2025 · Journal of Medical Internet Research
55. Hyperparameter Tuning and Automatic Image Augmentation for Deep Learning-Based Angle Classification on Intraoral Photographs—A Retrospective Study
    José Eduardo Cejudo Grano de Oro, Petra Julia Koch, Joachim Krois, Anselmo García Cantú Ros, Jay Sureshbhai Patel, Hendrik Meyer‐Lueckel, Falk Schwendicke · 2022 · Diagnostics
56. Performance of artificial intelligence using oral and maxillofacial CBCT images
    Fatma Badr, Fatima M. Jadu · 2022 · Nigerian Journal of Clinical Practice
57. Effect of selection bias on Automatic Colonoscopy Polyp Detection
    Palak, Harshita Mangotra, Nidhi Goel · 2023 · Biomedical Signal Processing and Control
58. Error mitigation enables PET radiomic cancer characterization on quantum computers
    Sasan Moradi, Clemens P. Spielvogel, Denis Krajnc, Christoph Brandner, Stefan Hillmich, Robert Wille, Tatjana Traub‐Weidinger, Xiang Li, Marcus Hacker, Wolfgang Drexler et al. · 2023 · European Journal of Nuclear Medicine and Molecular Imaging
59. Systematic review of artificial intelligence development and evaluation for MRI diagnosis of knee ligament or meniscus tears
    Samantha M. Santomartino, Justin E. Kung, Paul Hyunsoo Yi · 2023 · Skeletal Radiology
60. Performances of machine learning algorithms in discriminating sacroiliitis features on MRI: a systematic review
    Sun Jae Moon, Seulkee Lee, Jinseub Hwang, Jaejoon Lee, Seonyoung Kang, Hoon‐Suk Cha · 2023 · RMD Open
61. Deep learning for determining the difficulty of endodontic treatment: a pilot study
    Hamed Karkehabadi, Elham Khoshbin, Nikoo Ghasemi, Amal Mahavi, Hossein Mohammad‐Rahimi, Soroush Sadr · 2024 · BMC Oral Health
62. The accuracy and quality of image-based artificial intelligence for muscle-invasive bladder cancer prediction
    Chunlei He, Hui Xu, Enyu Yuan, Lei Ye, Yuntian Chen, Jin Yao, Bin Song · 2024 · Insights into Imaging
63. The Role of Radiomics in the Prediction of Clinically Significant Prostate Cancer in the PI-RADS v2 and v2.1 Era: A Systematic Review
    Andreu Antolín, Núria Rosón, Richard Mast, Javier Arce, Ramon Almodovar, Roger Cortada, Almudena Maceda, Manuel Escobar, Enrique Trilla, Juan Moróte · 2024 · Cancers
64. Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol
    Brendan S. Kelly, Conor S. Judge, Stephanie M. Bollard, Simon M. Clifford, Gerard M. Healy, Kristen W. Yeom, Aonghus Lawlor, Ronan P. Killeen · 2020 · Insights into Imaging
65. Checklist for Artificial Intelligence in Medical Imaging Reporting Adherence in Peer-Reviewed and Preprint Manuscripts With the Highest Altmetric Attention Scores: A Meta-Research Study
    Sivanesan, Umaseh, Wu, Kay, McInnes, Matthew D. F., Dhindsa, Kiret, Salehi, Fateme, van der Pol, Christian B. · 2023 · Canadian Association of Radiologists Journal
66. Application of Artificial Intelligence in Cone-Beam Computed Tomography for Airway Analysis: A Narrative Review
    Izzati Nabilah Ismail, Pram Kumar Subramaniam, Khairul Bariah Chi Adam, Ahmad Badruddin Ghazali · 2024 · Diagnostics
67. Brain MRI Image Super-Resolution Reconstruction: A Systematic Review
    Abdulhamid Muhammad, Supavadee Aramvith, Khanita Duangchaemkarn, Ming–Ting Sun · 2024 · IEEE Access
68. Machine Learning Algorithms to Predict the Risk of Rupture of Intracranial Aneurysms: a Systematic Review
    Karan Daga, Siddharth Agarwal, Zaeem Moti, Matthew B. K. Lee, Munaib Din, David A. Wood, Marc Modat A, Thomas Calvert Booth · 2024 · Clinical Neuroradiology
69. Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies
    Yero Samuel Ndiaye, Peter Cramton, Chavdar Chernev, Axel Ockenfels, Tobias Schwarz · 2025 · Frontiers in Veterinary Science
70. Comprehensive reporting guidelines and checklist for studies developing and utilizing artificial intelligence models
    Sang Gyu Kwak, Jonghae Kim · 2025 · Korean Journal of Anesthesiology
71. Artificial intelligence and sleep medicine II: A scoping review of applications, advancements, and future directions
    Haitham Jahrami, Waqar Husain, Khaled Trabelsi, Thomas Penzel, Max Hirshkowitz, Javad Razjouyan, Ahmed Salem BaHammam, Amir Sharafkhaneh · 2025 · Sleep Medicine Reviews
72. Independent evaluation of a multi-view multi-task convolutional neural network breast cancer classification model using Finnish mammography screening data
    Antti Isosalo, Satu I. Inkinen, Topias Turunen, Pieta S. Ipatti, Jarmo Reponen, Miika Tapio Nieminen · 2023 · Computers in Biology and Medicine
73. Identification of IDH and TERTp mutations using dynamic susceptibility contrast MRI with deep learning in 162 gliomas
    Buse Buz-Yalug, Gülce Turhan, Ayşe İrem Çetin, Sukru Samet Dindar, Ayça Erşen Danyeli, Cengiz Yakıcıer, Mustafa Necmettin Pamir, Koray Özduman, Alp Di̇nçer, Esin Öztürk-Işık · 2023 · European Journal of Radiology
74. Mortality Prediction of Patients with Subarachnoid Hemorrhage Using a Deep Learning Model Based on an Initial Brain CT Scan
    Sergio García-García, Santiago Cepeda, Dominik Müller, Alejandra Mosteiro, Ramón Torné, Silvia Agudo, Natalia de la Torre, Ignacio Arrese, Rosario Sarabia · 2023 · Brain Sciences
75. Deep learning for tooth identification and enumeration in panoramic radiographs
    Soroush Sadr, Hossein Mohammad‐Rahimi, Mohammad Soroush Ghorbanimehr, Rata Rokhshad, Zahra Abbasi, Parisa Soltani, Amirhossein Moaddabi, Shahriar Shahab, Mohammad Hossein Rohban · 2023 · Dental Research Journal
76. Choosing the right artificial intelligence solutions for your radiology department: key factors to consider
    Deniz Can Alis, Toygar Tanyel, Emine Meltem, Mustafa Ege Şeker, Delal Şeker, Hakkı Muammer Karakaş, Ercan Karaarslan, İlkay Öksüz · 2024 · Diagnostic and Interventional Radiology
77. A radiograph-based deep learning model improves radiologists’ performance for classification of histological types of primary bone tumors: A multicenter study
    Zhuoyao Xie, Huanmiao Zhao, Liwen Song, Qiang Ye, Liming Zhong, Shisi Li, Rui Zhang, Menghong Wang, Xiaqing Chen, Zixiao Lu et al. · 2024 · European Journal of Radiology
78. Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study
    Nyi Nyi Soe, Zhen Tao Yu, Phyu Mon Latt, David M. Lee, Ranjit S Samra, Zongyuan Ge, Rashidur Rahman, Jiajun Sun, Jason J. Ong, Christopher Kincaid Fairley et al. · 2024 · Journal of Medical Internet Research
79. Automation and Decision Support in the Area of Nephrology Using Numerical Algorithms, Artificial Intelligence, and Expert Approach: Review of the Current State of Knowledge
    Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel · 2024 · IEEE Access
80. A survey on cell nuclei instance segmentation and classification: Leveraging context and attention
    João D. Nunes, Diana Montezuma, Domingos Oliveira, Tânia Pereira, Jaime S. Cardoso · 2024 · Medical Image Analysis
81. Comparative analysis of deep learning algorithms for dental caries detection and prediction from radiographic images: a comprehensive umbrella review
    Mahmood Dashti, Jimmy Londono, Shohreh Ghasemi, Niusha Zare, Meyassara Samman, Heba Mahmoud Ashi, Mohammad Hosein Amirzade-Iranaq, Farshad Khosraviani, Mohammad A. Sabeti, Zohaib Khurshid · 2024 · PeerJ Computer Science
82. Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation
    Yosuke Yamagishi, Yuta Nakamura, Shouhei Hanaoka, Osamu Abe · 2025 · JMIR Cancer
83. Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques
    Luis Mariano Esteban, Ángel Borque‐Fernando, Maria Etelvina Escorihuela, Javier Esteban‐Escaño, J.M. Abascal Junquera, Pol Servián, Juan Moróte · 2025 · Scientific Reports
84. Reproducible Artificial Intelligence Research Requires Open Communication of Complete Source Code
    Felipe Kitamura, Ian Pan, Timothy Lee Kline · 2020 · Radiology Artificial Intelligence
85. Performance and Usability of Code-Free Deep Learning for Chest Radiograph Classification, Object Detection, and Segmentation
    Samantha M. Santomartino, Nima Hafezi‐Nejad, Vishwa S. Parekh, Paul Hyunsoo Yi · 2023 · Radiology Artificial Intelligence
86. AI-Enhanced PET and MR Imaging for Patients with Breast Cancer
    Valeria Romeo, Linda P. Moy, Katja Pinker · 2023 · PET Clinics
87. Artificial Intelligence–Powered Technologies for the Management of Vascular Diseases: Building Guidelines and Moving Forward Evidence Generation
    Fabien Lareyre, Anders Wanhainen, Juliette Raffort · 2023 · Journal of Endovascular Therapy
88. A Narrative Review of Artificial Intelligence in MRI-Guided Prostate Cancer Diagnosis: Addressing Key Challenges
    Deniz Can Alis, Aslıhan Onay, Evrim Çolak, Ercan Karaarslan, Barış Bakır · 2025 · Diagnostics
89. Deep Learning for Detecting Dental Plaque and Gingivitis From Oral Photographs: A Systematic Review
    Mohammad Moharrami, Elaheh Vahab, Mobina Bagherianlemraski, Ghazal Hemmati, Sonica Singhal, Carlos Quiñonez, Falk Schwendicke, Michael Glogauer · 2025 · Community Dentistry And Oral Epidemiology
90. Development of lumbar spine MRI referrals vetting models using machine learning and deep learning algorithms: Comparison models vs healthcare professionals
    A.H. Alanazi, Andrea Cradock, Louise A. Rainford · 2022 · Radiography
91. A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia
    Camilla Scapicchio, A. Chincarini, Elena Ballante, Luca Berta, Eleonora Bicci, Chandra Bortolotto, Francesca Brero, Raffaella Fiamma Cabini, Giuseppe Cristofalo, Salvatore Claudio Fanni et al. · 2023 · European Radiology Experimental
92. Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings
    Jim Zhong, R. Frood, A. McWilliam, A. Davey, J. Shortall, M. Swinton, O. Hulson, C. West, D. Buckley, Sarah Brown et al. · 2023 · La radiologia medica
93. Impact of deep learning on radiologists and radiology residents in detecting breast cancer on CT: a cross-vendor test study
    Koichiro Yasaka, C. Sato, H. Hirakawa, N. Fujita, Mineo Kurokawa, Yusuke Watanabe, T. Kubo, Osamu Abe · 2023 · Clinical Radiology
94. Deep Learning-Based Localization and Detection of Malpositioned Endotracheal Tube on Portable Supine Chest Radiographs in Intensive and Emergency Medicine: A Multicenter Retrospective Study*
    Chih‐Hung Wang, Tianyu Hwang, Yu‐Sen Huang, Joyce Tay, Ching‐Yi Wu, Meng‐Che Wu, Holger R. Roth, Dong Yang, Can Zhao, Weichung Wang et al. · 2023 · Critical Care Medicine
95. Artificial intelligence in healthcare: why not apply the medico-legal method starting with the Collingridge dilemma?
    Rossana Cecchi, Tudor Mihai Haja, Francesco Calabrò, Iben Fasterholdt, Benjamin Schnack Rasmussen · 2024 · International Journal of Legal Medicine
96. Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review
    Frédéric Panthier, Alberto Melchionna, Hugh Crawford‐Smith, Yiannis Phillipou, Simon K. S. Choong, Vimoshan Arumuham, Siân Allen, CLARE M. ALLEN, Daron Smith · 2024 · Journal of Endourology
97. Evaluating artificial intelligence for medical imaging: a primer for clinicians
    Shivank Keni · 2024 · British Journal of Hospital Medicine
98. Deep learning-based breast MRI for predicting axillary lymph node metastasis: a systematic review and meta-analysis
    Chia-Fen Lee, Joseph Lin, Yu-Len Huang, Shou-Tung Chen, Chen‐Te Chou, Dar-Ren Chen, Wen-Pei Wu · 2025 · Cancer Imaging
99. Artificial Intelligence in Prostate MRI: Current Evidence and Clinical Translation Challenges—A Narrative Review
    Vlad-Octavian Bolocan, Alexandru Mitoi, Oana Nicu-Canareica, Maria-Luiza Băean, Cosmin Medar, Gelu-Adrian Popa · 2025 · Journal of Imaging
100. Robust radiomics: a review of guidelines for radiomics in medical imaging
     M. Avanzo, P. Soda, Marco Bertolini, A. Bettinelli, T. Rancati, J. Stancanello, Osvaldo Rampado, G. Pirrone, Annalisa Drigo · 2026 · Frontiers in Radiology