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

Cited by (1,001)

Items 501–600 of 1,001

1. Robust radiomics: a review of guidelines for radiomics in medical imaging
   Michele Avanzo, P. Soda, Marco Bertolini, Andrea Bettinelli, T. Rancati, Joseph Stancanello, Osvaldo Rampado, Giovanni Pirrone, Annalisa Drigo · 2026 · Frontiers in Radiology
2. Framework for Assessing Ethical Aspects of Algorithms and Their Encompassing Socio-Technical System
   Xadya van Bruxvoort, Maurice van Keulen · 2021 · Applied Sciences
3. The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment
   Gaia Spadarella, Lorenzo Ugga, Giuseppina Calareso, Rossella Villa, Serena D’Aniello, Renato Cuocolo · 2022 · Neuroradiology
4. Artificial Intelligence in Oncological Hybrid Imaging
   Benedikt Feuerecker, Maurice M. Heimer, Thomas Geyer, Matthias Philipp Fabritius, Sijing Gu, Balthasar Maria Schachtner, Leonie Beyer, Jens Ricke, Sergios Gatidis, Michael Ingrisch et al. · 2022 · RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren
5. Applications of artificial intelligence in magnetic resonance imaging of primary pediatric cancers: a scoping review and CLAIM score assessment
   Brian Tsang, Aaryan Gupta, Marcelo Straus Takahashi, Henrique Coimbra Baffi, Tolulope Ola, Andrea Schwarz Doria · 2023 · Japanese Journal of Radiology
6. Detection of dental restorations using no-code artificial intelligence
   Manal H. Hamdan, Zaid Badr, Jennifer Bjork, Reagan Saxe, Francesca Malensek, Caroline R. Miller, Rakhi Shah, Shengtong Han, Hossein Mohammad‐Rahimi · 2023 · Journal of Dentistry
7. The impact of artificial intelligence on Ukrainian medicine: benefits and challenges for the future
   Nina Sofilkanych, Olena Vesova, Valeriy Kaminskyy, Anna Kryvosheieva · 2023 · Futurity Medicine.
8. Deep Learning–based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study
   Chih‐Hung Wang, Weishan Chang, Meng‐Rui Lee, Joyce Tay, Ching‐Yi Wu, Meng‐Che Wu, Holger R. Roth, Dong Heon Yang, Can Zhao, Weichung Wang et al. · 2024 · Journal of Imaging Informatics in Medicine
9. Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach
   Riccardo Cau, Francesco Pisu, Alessandra Pintus, Vitanio Palmisano, Roberta Montisci, Jasjit S. Suri, Rodrigo A. Salgado, Luca Saba · 2024 · European Radiology
10. Evaluation of a BERT Natural Language Processing Model for Automating CT and MRI Triage and Protocol Selection
    Jason Yao, Abdullah Alabousi, Oleg Mironov · 2024 · Canadian Association of Radiologists Journal
11. Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans – A systematic review
    Saana M. Mäenpää, Miikka Korja · 2024 · International Journal of Medical Informatics
12. Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study
    Louloua Mourad, Nayer S. AboElsaad, Wael M. Talaat, Nada M.H. Fahmy, Hams Abdelrahman, Yehia A. El-Mahallawy · 2024 · Journal of Stomatology Oral and Maxillofacial Surgery
13. Deep Learning for Staging Periodontitis Using Panoramic Radiographs
    Xin Li, Kejia Chen, Dan Zhao, Yongqi He, Yajie Li, Zeliang Li, Xiangyu Guo, Chunmei Zhang, Wenbin Li, Songlin Wang · 2025 · Oral Diseases
14. The Role of AI in the Evaluation of Neuroendocrine Tumors: Current State of the Art
    Felipe Lopez-Ramirez, Mohammad Yasrab, Florent Tixier, Satomi Kawamoto, Elliot K. Fishman, Linda Chi Hang Chu · 2025 · Seminars in Nuclear Medicine
15. Enhancing Reliability in Medical Image Classification of Imperfect Views
    Wei Liu, Yufei Chen, Xiaodong Yue, Changqing Zhang, Shaorong Xie · 2025 · IEEE Transactions on Circuits and Systems for Video Technology
16. Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example
    Elsa D. Angelini, Anand Shah · 2021 · Mycopathologia
17. Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network
    Adrian Jonathan Wilder-Smith, Shan Yang, Thomas Weikert, Jens Bremerich, Philip Haaf, Martin Segeroth, Lars Christian Ebert, Alexander Walter Sauter, Raphael Sexauer · 2022 · Diagnostics
18. A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates
    Nadja Gruber, Malik Galijašević, Milovan Regodić, Astrid Ellen Grams, Christian Siedentopf, Ruth Steiger, Marlene Hammerl, Markus Haltmeier, Elke Ruth Gizewski, Tanja Janjic · 2022 · Artificial Intelligence in Medicine
19. DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy
    Brendan S. Kelly, Mesha L Martinez, Huy M. Do, Joel Hayden, Yuhao Huang, Vivek Srikar Yedavalli, Chang Yueh Ho, Pearse Andrew Keane, Ronan P. Killeen, Aonghus Lawlor et al. · 2023 · European Radiology
20. Meta-analysis of deep learning approaches for automated coronary artery calcium scoring: Performance and clinical utility AI in CAC scoring: A meta-analysis
    Wang, Ting-Wei, Tzeng, Yun-Hsuan, Wu, Kuan-Ting, Liu, Ho-Ren, Hong, Jia-Sheng, Hsu, Huan-Yu, Fu, Hao-Neng, Lee, Yung-Tsai, Yin, Wei-Hsian, Wu, Yu-Te · 2024 · Computers in Biology and Medicine
21. A deep learning-based cascade algorithm for pancreatic tumor segmentation
    Dandan Qiu, Jianguo Ju, Shumin Ren, Tongtong Zhang, Huijuan Tu, Xin Tan, Fei Xie · 2024 · Frontiers in Oncology
22. Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis
    Mohsen Salimi, Shakiba Houshi, Ali Gholamrezanezhad, Pouria Vadipour, Sharareh Seifi · 2025 · Clinical Imaging
23. AspectFL: Aspect-Oriented Programming for Trustworthy and Compliant Federated Learning Systems
    Anas Alsobeh, Amani Shatnawi, Aws Abed Al Raheem Magableh · 2025 · Information
24. Localization-adjusted diagnostic performance and assistance effect of a computer-aided detection system for pneumothorax and consolidation
    Sun Yeop Lee, Sangwoo Ha, Min Gyeong Jeon, Hao Li, Hyunju Choi, Hwa Pyung Kim, Ye Ra Choi, I Hoseok, Yeon Joo Jeong, Yoon Ha Park et al. · 2022 · npj Digital Medicine
25. The role of artificial intelligence in veterinary radiation oncology
    Del M. Leary, Parminder S. Basran · 2022 · Veterinary Radiology & Ultrasound
26. Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions
    Destie Provenzano, Oleksiy Melnyk, Danish Imtiaz, Benjamin McSweeney, Daniel Nemirovsky, Michael Wynne, Michael Joseph Whalen, Yuan James Rao, Murray H. Loew, Shawn Haji-Momenian · 2023 · Applied Sciences
27. Improving accuracy of early dental carious lesions detection using deep learning-based automated method
    Paula Dresch Portella, Lucas Ferrari de Oliveira, Mateus Felipe de Cássio Ferreira, Bruna Cristine Dias, Juliana Feltrin de Souza, Luciana Reichert da Silva Assunção · 2023 · Clinical Oral Investigations
28. Challenges of Machine Learning and AI (What Is Next?), Responsible and Ethical AI
    Polyxeni Gkontra, Gianluca Quaglio, Anna Tselioudis Garmendia, Karim Lekadir · 2023 · Springer eBooks
29. Clinical Evaluation of Deep Learning for Tumor Delineation on18F-FDG PET/CT of Head and Neck Cancer
    David Gergely Kovacs, Claes Nøhr Ladefoged, Kim Francis Andersen, Jane Maestri Brittain, Charlotte Birk Christensen, Danijela Dejanović, Naja Liv Hansen, Annika Loft, Jørgen Holm Petersen, Michala Holm Reichkendler et al. · 2024 · Journal of Nuclear Medicine
30. Radiogenomic biomarkers for immunotherapy in glioblastoma: A systematic review of magnetic resonance imaging studies
    Prajwal Ghimire, Ben Kinnersley, Golestan Karami, Prabhu Arumugam, Richard S. Houlston, Keyoumars Ashkan, Marc Modat A, Thomas Calvert Booth · 2024 · Neuro-Oncology Advances
31. AI-accelerated prostate MRI: a systematic review
    Ciaran Reinhardt, Hayley Briody, Peter J MacMahon · 2024 · British Journal of Radiology
32. Large-scale pretrained frame generative model enables real-time low-dose DSA imaging: An AI system development and multi-center validation study
    Huangxuan Zhao, Ziyang Xu, Lei Chen, Linxia Wu, Ziwei Cui, Jinqiang Ma, Tao Sun, Yu Lei, Nan Wang, Hongyao Hu et al. · 2024 · Med
33. Reporting standards to support cost-effectiveness evaluations of AI-driven health care
    Jamie Elvidge, Dalia Dawoud · 2024 · The Lancet Digital Health
34. Radiomics in distinguishing between lung adenocarcinoma and lung squamous cell carcinoma: a systematic review and meta-analysis
    Lili Shi, Jinli Zhao, Zhichao Wei, Huiqun Wu, Meihong Sheng · 2024 · Frontiers in Oncology
35. Impact of metadata in multimodal classification of bone tumours
    Florian Hinterwimmer, Michael Guenther, Sarah Consalvo, Jan Neumann, Alexandra S. Gersing, Klaus Woertler, Rüdiger von Eisenhart‐Rothe, Rainer Burgkart, Daniel Rueckert · 2024 · BMC Musculoskeletal Disorders
36. Artificial intelligence for the analysis of intracoronary optical coherence tomography images: a systematic review
    Ruben G.A. van der Waerden, Rick H. J. A. Volleberg, Thijs J. Luttikholt, Pierandrea Cancian, Joske L. van der Zande, Gregg W. Stone, Niels Ramsing Holm, Elvin Kedhi, Javier Escaned, Dario Pellegrini et al. · 2025 · European Heart Journal - Digital Health
37. Multimodal Artificial Intelligence Model for Prediction of Abdominal Aortic Aneurysm Shrinkage After Endovascular Repair ( the ART in EVAR study).
    R. V. van Rijswijk, M. Bogdanovic, J. Roy, K. Yeung, C. Zeebregts, R. H. Geelkerken, E. Groot Jebbink, J. Wolterink, M. Reijnen · 2025 · Journal of Endovascular Therapy
38. Incidence Lung Cancer after a Negative CT Screening in the National Lung Screening Trial: Deep Learning-Based Detection of Missed Lung Cancers
    Jungheum Cho, Jihang Kim, Kyong Joon Lee, Chang-Mo Nam, Sung Hyun Yoon, Hwayoung Song, Junghoon Kim, Ye Ra Choi, Kyung Hee Lee, Kyung Won Lee · 2020 · Journal of Clinical Medicine
39. Developing and Validating Multi-Modal Models for Mortality Prediction in COVID-19 Patients: a Multi-center Retrospective Study
    Joy Tzung-Yu Wu, Miguel Ángel Armengol de la Hoz, Po‐Chih Kuo, Joseph Alexander Paguio, Jasper Seth Yao, Edward Christopher Dee, Wesley Lok Kin Yeung, Jerry Jurado, Achintya N. Moulick, Carmelo Milazzo et al. · 2022 · Journal of Imaging Informatics in Medicine
40. Diffusion-weighted MRI with deep learning for visualizing treatment results of MR-guided HIFU ablation of uterine fibroids
    Derk Jan Slotman, Lambertus W. Bartels, Aylene Zijlstra, Inez M. Verpalen, Jochen A. C. van Osch, Ingrid M. Nijholt, Edwin Heijman, Miranda van ‘t Veer-ten Kate, Erwin de Boer, Rolf D. van den Hoed et al. · 2022 · European Radiology
41. Artificial Intelligence Enabled Sustainable Education System Using Vedic Scripture and Cyber Security
    Sachin Sharma, Aanika Gupta, Ranu Tyagi · 2023 · International Conference on Advances in Computational Intelligence and Communication (ICACIC)
42. Meta-research on reporting guidelines for artificial intelligence: are authors and reviewers encouraged enough in radiology, nuclear medicine, and medical imaging journals?
    Koçak, Burak, Keleş, Ali, Köse, Fadime · 2024 · Diagnostic and Interventional Radiology
43. Automatic deep learning segmentation of mandibular periodontal bone topography on cone-beam computed tomography images
    Dániel Palkovics, Bálint Molnár, Csaba Pintér, David García‐Mato, Andres Diaz‐Pinto, Péter Windisch, Christoph A. Ramseier · 2025 · Journal of Dentistry
44. Guidelines for Reporting Studies on Large Language Models in Radiology: An International Delphi Expert Survey
    Jonathan Kottlors, Andra-Iza Iuga, Christian Blüthgen, Keno K. Bressem, Jakob Nikolas Kather, Linda P. Moy, Christoph Wald, Wei Wang, Tianming Liu, Erik R. Ranschaert et al. · 2026 · Radiology
45. Automatic segmentation of peripheral arteries and veins in ferumoxytol‐enhanced MR angiography
    Vahid Ghodrati, Yair Rivenson, Ashley Elizabeth Prosper, Kevin d. Haan, Fadil Ali, Takegawa Yoshida, Arash Bedayat, Kim‐Lien Nguyen, J. Paul Finn, Peng Hu · 2021 · Magnetic Resonance in Medicine
46. Predictive value of clot imaging in acute ischemic stroke: A systematic review of artificial intelligence and conventional studies
    Daniela Dumitriu LaGrange, Jérémy Hofmeister, Andrea Rosi, María Isabel Vargas, Isabel Wanke, Paolo Machi, Karl‐Olof Lövblad · 2022 · Neuroscience Informatics
47. Reporting Quality of Research Studies on AI Applications in Medical Images According to the CLAIM Guidelines in a Radiology Journal With a Strong Prominence in Asia
    D. Kim, Hyun Woo Oh, Chong Hyun Suh · 2023 · Korean Journal of Radiology
48. Applied deep learning in neurosurgery: identifying cerebrospinal fluid (CSF) shunt systems in hydrocephalus patients
    Thomas Rhomberg, Felipe A. Trivik-Barrientos, Arsany Hakim, Andreas Raabe, Michael K. Murek · 2024 · Acta Neurochirurgica
49. Recommender-based bone tumour classification with radiographs—a link to the past
    Florian Hinterwimmer, Ricardo Smits Serena, Nikolas Wilhelm, Sebastian Breden, Sarah Consalvo, Fritz Seidl, Dominik Jüstel, Rainer Burgkart, Klaus Woertler, Rüdiger von Eisenhart‐Rothe et al. · 2024 · European Radiology
50. Computer Vision and Videomics in Otolaryngology–Head and Neck Surgery
    Alberto Paderno, Nikita Bedi, Anita Rau, F. Christopher Holsinger · 2024 · Otolaryngologic Clinics of North America
51. Deep Learning Models for Aorta Segmentation in Computed Tomography Images: A Systematic Review And Meta-Analysis
    Tingwei Wang, Yun-Hsuan Tzeng, Jia‐Sheng Hong, Ho-Ren Liu, Kuan-Ting Wu, Hao-Neng Fu, Yung‐Tsai Lee, Wei‐Hsian Yin, Yu‐Te Wu · 2024 · Journal of Medical and Biological Engineering
52. Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR
    Philippe Germain, Armine Vardazaryan, Nicolas Padoy, Aïssam Labani, Catherine Roy, Thomas Hellmut Schindler, Soraya El Ghannudi · 2021 · Diagnostics
53. Artificial Intelligence for COVID-19 Detection in Medical Imaging—Diagnostic Measures and Wasting—A Systematic Umbrella Review
    Paweł Jemioło, Dawid Storman, Patryk Orzechowski · 2022 · Journal of Clinical Medicine
54. Enhanced Patient-Centricity: How the Biopharmaceutical Industry Is Optimizing Patient Care through AI/ML/DL
    Kelly H. Zou, Jim Z. Li · 2022 · Healthcare
55. Focus on machine learning models in medical imaging
    Giorgos Papanastasiou, Alba García Seco de Herrera, Chengjia Wang, Heye Zhang, Guang Yang, Ge Wang · 2022 · Physics in Medicine and Biology
56. Assessment of a combined musculoskeletal and chest deep learning-based detection solution in an emergency setting
    Alexandre Parpaleix, Clémence Parsy, Marina Cordari, Mehdi Mejdoubi · 2023 · European Journal of Radiology Open
57. Radiologist-Trained AI Model for Identifying Suboptimal Chest-Radiographs
    Giridhar Dasegowda, Bernardo Canedo Bizzo, Reya V. Gupta, Parisa Kaviani, Shadi Ebrahimian, Debra Ricciardelli, Faezeh Abedi-Tari, Nir Neumark, Subba Rao Digumarthy, Mannudeep K. Kalra et al. · 2023 · Academic Radiology
58. Artificial intelligence: advances and pitfalls
    Falk Schwendicke, Martha Büttner · 2023 · BDJ
59. The current state of artificial intelligence research in pediatric radiology and recommendations for the future: a scoping review
    Rakhshan Kamran, Elysa Widjaja, Alex Sy, Jessica Bosso, Lalit Choudhary, Alexandra Lawrynuik, Yi Jin, Cynthia Chan, Nasana Vaidya, Sarah Larrigan et al. · 2026 · Pediatric Radiology
60. Performance of predictive AI-based clinical decision support systems across clinical domains: A systematic review and meta-analysis
    William J. Waldock, Ahmad Guni, Ara Wardkes Darzi, Hutan Ashrafian · 2026 · PLOS Digital Health
61. An artificial intelligence algorithm for the classification of sphenoid sinus pneumatisation on sinus computed tomography scans
    Alon Taylor, Al-Rahim R. Habib, Ashnil Kumar, Eugene H. Wong, Zubair Hasan, Narinder Pal Singh · 2023 · Clinical Otolaryngology
62. Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography
    Ketki K. Kinkar, Brandon K.K. Fields, Mary W. Yamashita, Bino Abel Varghese · 2024 · Frontiers in Radiology
63. Challenges and Potential of Artificial Intelligence in Neuroradiology
    Anthony J. Winder, Emma A. M. Stanley, Jens Fiehler, Nils D. Forkert · 2024 · Clinical Neuroradiology
64. Assessment of bias in scoring of AI-based radiotherapy segmentation and planning studies using modified TRIPOD and PROBAST guidelines as an example
    Coen Hurkmans, Jean‐Emmanuel Bibault, E. Clementel, Jennifer Dhont, Wouter van Elmpt, Georgios Kantidakis, Nicolaus H. Andratschke · 2024 · Radiotherapy and Oncology
65. Exploring the Methodological Approaches of Studies on Radiographic Databases Used in Cariology to Feed Artificial Intelligence: A Systematic Review
    Amadou Diaw Ndiaye, Marie-Agnès Gasqui, Fabien Millioz, Matthieu Pérard, Fatou Lèye-Benoist, Brigitte Grosgogeat · 2024 · Caries Research
66. Applications of Deep Learning Models on the Medical Images of Osteonecrosis of the Femoral Head (ONFH): A Comprehensive Review
    Jiao Wang, Yi Zheng, Jun Luo, Timothy Tin‐Yan Lee, Pengfei Li, Yingqi Zhang, James Chung‐Wai Cheung, Duo Wai‐Chi Wong, Ming Ni · 2024 · IEEE Access
67. One novel transfer learning-based CLIP model combined with self-attention mechanism for differentiating the tumor-stroma ratio in pancreatic ductal adenocarcinoma
    Hongfan Liao, Jiang Yuan, Chunhua Liu, Jiao Zhang, Yaying Yang, Hongwei Liang, Haotian Liu, Shanxiong Chen, Yongmei Li · 2024 · La radiologia medica
68. RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models
    Farhad Maleki, Linda P. Moy, Reza Forghani, Tapotosh Ghosh, Katie L. Ovens, Steve G. Langer, Pouria Rouzrokh, Bardia Khosravi, Ali Ganjizadeh, Daniel Warren et al. · 2024 · Journal of Imaging Informatics in Medicine
69. Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol
    Susan Cheng Shelmerdine, Cato Pauling, Emma Allan, Dean Langan, Emily Ashworth, Ka-Wai Yung, Joy L. Barber, Saira Haque, David Rosewarne, Nick Woznitza et al. · 2024 · BMJ Open
70. Prostate cancer MRI methodological radiomics score: a EuSoMII radiomics auditing group initiative
    Armando Ugo Cavallo, Arnaldo Stanzione, Andrea Ponsiglione, Romina Trotta, Salvatore Claudio Fanni, Samuele Ghezzo, Federica Vernuccio, Michail E. Klontzas, Matthaios Triantafyllou, Lorenzo Ugga et al. · 2024 · European Radiology
71. Textual Proficiency and Visual Deficiency: A Comparative Study of Large Language Models and Radiologists in MRI Artifact Detection and Correction
    Yasin Celal Güneş, Turay Cesur, Eren Çamur, Bilal Egemen Çifçi, Turan Kaya, Mehmet Numan Colakoglu, Ural Koç, Rıza Sarper Ökten · 2025 · Academic Radiology
72. AI as teacher: effectiveness of an AI-based training module to improve trainee pediatric fracture detection
    Sean O’Rourke, Sophia Xu, Stephanie Carrero, Harrison M. Drebin, Ariel Felman, Andrew Ko, Adam Misseldine, Sofia Mouchtaris, Brett Musialowicz, Tony T. Wong et al. · 2025 · Skeletal Radiology
73. Role of Artificial Intelligence in Detecting and Classifying Aortic Dissection: Where Are We? A Systematic Review and Meta-Analysis
    Ashar Asif, Maha Alsayyari, Dorothy Monekosso, Paolo Remagnino, Raghuram Lakshminarayan · 2025 · Radiology Cardiothoracic Imaging
74. Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol
    Nita Mulliqi, Anders Blilie, Xiaoyi Ji, Kelvin Szolnoky, Henrik Olsson, Matteo Titus, Geraldine Martinez Gonzalez, Sol Erika Boman, Masi Valkonen, Einar G. Gudlaugsson et al. · 2025 · BMJ Open
75. Validation of a machine learning software tool for automated large vessel occlusion detection in patients with suspected acute stroke
    Petra Cimflová, Rotem Golan, Johanna Maria Ospel, Alireza Sojoudi, Chris C. Duszynski, Ibukun Elebute, Houssam El‐Hariri, Seyed Hossein Mousavi, Luis A. Souto Maior Neto, Najratun Nayem Pinky et al. · 2022 · Neuroradiology
76. Multi-center validation of an artificial intelligence system for detection of COVID-19 on chest radiographs in symptomatic patients
    Michael Kuo, Keith Wan-Hang Chiu, D.S. Wang, Anna Rita Larici, Dmytro Poplavskiy, Adele Valentini, Alessandro Napoli, Andrea Borghesi, Guido Ligabue, Benjamin Fang et al. · 2022 · European Radiology
77. The Role of Artificial Intelligence in Predicting Outcomes by Cardiovascular Magnetic Resonance: A Comprehensive Systematic Review
    Hosamadin S. Assadi, Samer Alabed, Ahmed Maiter, Mahan Salehi, Rui Li, David Paul Ripley, Rob J. van der Geest, Yumin Zhong, Liang Zhong, Andrew J. Swift et al. · 2022 · Medicina
78. Deep Learning for Detection of Pneumothorax and Pleural Effusion on Chest Radiographs
    Ali Shah Tejani, Thomas Dowling, Sreeja Sanampudi, Rana M. Yazdani, Arzu Canan, Elona Malja, Yin Xi, Suhny Abbara, Ronald M. Peshock, Fernando Uliana Kay · 2023 · Journal of Thoracic Imaging
79. AI-Generated Images as an Emergent Record Format
    Jessica Bushey · 2023 · IEEE International Conference on Big Data (BigData)
80. Intraoral radiograph anatomical region classification using neural networks
    Nikolaos Kyventidis, Christos Angelopoulos · 2021 · International Journal of Computer Assisted Radiology and Surgery
81. Machine learning identifies factors related to early joint space narrowing in dysplastic and non-dysplastic hips
    Michail E. Klontzas, Emmanouil Volitakis, Üstün Aydıngöz, Konstantinos Chlapoutakis, Apostolos H. Karantanas · 2021 · European Radiology
82. An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer
    Yu-quan Wu, Ruizhi Gao, Peng Lin, Rong Wen, Haiyuan Li, Meiyan Mou, Fenghuan Chen, Fen Huang, Weijie Zhou, Hong Yang et al. · 2022 · BMC Medical Imaging
83. Using Segment Anything Model 2 for Zero-Shot 3D Segmentation of Abdominal Organs in Computed Tomography Scans to Adapt Video Tracking Capabilities for 3D Medical Imaging: Algorithm Development and Validation
    Yosuke Yamagishi, Shouhei Hanaoka, Tomohiro Kikuchi, Takahiro Nakao, Yuta Nakamura, Yukihiro Nomura, Soichiro Miki, T. Yoshikawa, Osamu Abe · 2025 · JMIR AI
84. Guidance for reporting artificial intelligence technology evaluations for ultrasound scanning in regional anaesthesia ( GRAITE ‐ USRA ): an international multidisciplinary consensus reporting framework
    Xiaoxi Zhang, Jenny Ferry, David W. Hewson, Professor Gary S. Collins, Matthew D. Wiles, Yi Zhao, Alexander P. L. Martindale, Michael Tomaschek, James Simeon Bowness, the GRAITE‐USRA Working Group · 2025 · Anaesthesia
85. Deep Learning Algorithms to Detect Fractures: Systematic Review Shows Promising Results but Many Limitations
    Jérémie F. Cohen, Matthew D. F. McInnes · 2022 · Radiology
86. A radiomics model based on preoperative gadoxetic acid–enhanced magnetic resonance imaging for predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma
    Changfeng Li, Qiang Wang, Mengda Zou, Ping Cai, Xuesong Li, Kai Feng, Leida Zhang, Ernesto Sparrelid, Torkel B. Brismar, Kuansheng Ma · 2023 · Frontiers in Oncology
87. Predicting rectal cancer tumor budding grading based on MRI and CT with multimodal deep transfer learning: A dual-center study
    Ziyan Liu, Jianye Jia, Fan Bai, Yuxin Ding, Lei Han, Genji Bai · 2024 · Heliyon
88. Perspectives on technology: Prostate Imaging‐Reporting and Data System ( PI ‐ RADS) interobserver variability
    Michio D. Taya, Spencer C. Behr, Antonio C. Westphalen · 2024 · British Journal of Urology
89. Trends and Public Perception of Artificial Intelligence in Medical Imaging: A Social Media Analysis
    Mansour A. Almanaa · 2024 · Cureus
90. Can ChatGPT4-vision identify radiologic progression of multiple sclerosis on brain MRI?
    Brendan S. Kelly, Sophie M. Duignan, Prateek Mathur, Henry Dillon, Edward H. Lee, Kristen W. Yeom, Pearse Andrew Keane, Aonghus Lawlor, Ronan P. Killeen · 2025 · European Radiology Experimental
91. Deep Learning for Lumbar Disc Herniation Diagnosis and Treatment Decision-Making Using Magnetic Resonance Imagings: A Retrospective Study
    Yuanlong He, He Xiang Zhong, Yong Qiu, Zheng Liu, Ai‐Bing Huang, Chunmao Chen, Jian Bian · 2025 · World Neurosurgery
92. How to read a paper involving artificial intelligence (AI)
    H Paul Dijkstra, Trisha Greenhalgh, Yosra Magdi Mekki, Jessica Morley · 2025 · BMJ Medicine
93. Wearable device for axillary lymph node screening in breast cancer based on infrared thermography and artificial intelligence
    Xiaoying Zhong, Jinqiu Deng, Lu Ping, Zhichao Zuo, Yu Zhao, Yidong Zhou, Xuefei Wang · 2025 · Breast Cancer Research
94. Incorporating Artificial Intelligence into Fracture Risk Assessment: Using Clinical Imaging to Predict the Unpredictable
    Sung Hye Kong · 2025 · Endocrinology and Metabolism
95. Next-Generation Advances in Prostate Cancer Imaging and Artificial Intelligence Applications
    Kathleen H. Miao, Julia H. Miao, Mark Finkelstein, Aritrick Chatterjee, Aytekin Oto · 2025 · Journal of Imaging
96. Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization
    Edward Korot, Mariana Batista Gonçalves, Saad Mahmud Khan, Robbert Struyven, Siegfried K. Wagner, Pearse Andrew Keane · 2021 · Current Opinion in Ophthalmology
97. Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review
    Ashley Gillman, Febrio Lunardo, Joseph Prinable, Gregg Belous, Aaron Nicolson, Hang Min, Andrew Terhorst, Jason Dowling · 2021 · Physical and Engineering Sciences in Medicine
98. Quality of Multicenter Studies Using MRI Radiomics for Diagnosing Clinically Significant Prostate Cancer: A Systematic Review
    Jeroen Bleker, Thomas Christian Kwee, Derya Yakar · 2022 · Life
99. Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature
    Pouria Rouzrokh, Bardia Khosravi, Sanaz Vahdati, Mana Moassefi, Shahriar Faghani, Elham Mahmoudi, Hamid Chalian, Bradley James Erickson · 2022 · Current Radiology Reports
100. How should studies using AI be reported? lessons from a systematic review in cardiac MRI
     Ahmed Maiter, Mahan Salehi, Andrew J. Swift, Samer Alabed · 2023 · Frontiers in Radiology