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

Cited by (1,001)

Items 701–800 of 1,001

1. Prognostic models for knee osteoarthritis: a protocol for systematic review, critical appraisal, and meta-analysis
   Jingyu Zhong, Liping Si, Guangcheng Zhang, Jiayu Huo, Yue Xing, Yangfan Hu, Huan Zhang, Weiwu Yao · 2021 · Systematic Reviews
2. Reporting of Model Performance and Statistical Methods in Studies That Use Machine Learning to Develop Clinical Prediction Models: Protocol for a Systematic Review
   Colin Weaver, Robert Barkev Basmadjian, Tyler S. Williamson, Kerry McBrien, Tolulope T. Sajobi, Devon J. Boyne, Mohamed Yusuf, Paul Everett Ronksley · 2022 · JMIR Research Protocols
3. Leveraging MRI characterization of longitudinal tears of the deep digital flexor tendon in horses using machine learning
   Ahmed N. ELKhamary, Erin K. Keenihan, Lauren Virginia Schnabel, W. Rich Redding, Jim Schumacher · 2022 · Veterinary Radiology & Ultrasound
4. Analysis of radiomic features derived from post-contrast T1-weighted images and apparent diffusion coefficient (ADC) maps for breast lesion evaluation: A retrospective study
   Nikolaos Stogiannos, Haralabos Bougias, E. Georgiadou, Stephanos Leandrou, Periklis Papavasileiou · 2023 · Radiography
5. Clinical Annotation and Segmentation Tool (CAST) Implementation for Dental Diagnostics
   Taseef Hasan Farook, Farhan Hasin Saad, Saif Ahmed, James Dudley · 2023 · Cureus
6. Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation
   Marco Dioguardi Burgio, Lorenzo Garzelli, Roberto Cannella, Maxime Ronot, Valérie Vilgrain · 2023 · Life
7. Comparison of an AI-Generated Case Report With a Human-Written Case Report: Practical Considerations for AI-Assisted Medical Writing
   Denver Steven Pinto, Sharon M Noronha, Gaurav M. Saigal, Robert M. Quencer · 2024 · Cureus
8. A comparison of Covid-19 early detection between convolutional neural networks and radiologists
   Alberto Albiol, Francisco Albiol, Roberto Paredes, Juana María Plasencia-Martínez, Ana Blanco Barrio, J.M. García Santos, Salvador Tortajada, Victoria M. González Montaño, Clara Rodríguez Godoy, Saray Fernández Gómez et al. · 2022 · Insights into Imaging
9. To buy or not to buy - Evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
   Patrick Omoumi · 2021
10. Machine learning in translation
    2021 · Nature Biomedical Engineering
11. To BERT or not to BERT: advancing non-invasive prediction of tumor biomarkers using transformer-based natural language processing (NLP)
    Ali Shah Tejani · 2023 · European Radiology
12. Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery
    Kuno, Masahiro, Osumi, Hiroki, Udagawa, Shohei, Yoshikawa, Kaoru, Ooki, Akira, Shinozaki, Eiji, Ishikawa, Tetsuo, Oba, Junna, Yamaguchi, Kensei, Sakurada, Kazuhiro · 2025 · Current Oncology
13. Current Status and Future of Artificial Intelligence in MM Imaging: A Systematic Review
    Ehsan Alipour, Atefe Pooyan, Firoozeh Shomal Zadeh, Azad Duke Darbandi, Pietro Andrea Bonaffini, Majid Chalian · 2023 · Diagnostics
14. Radiomics in Musculoskeletal Tumors
    Daniel Brandenberger, Lawrence M. White · 2024 · Seminars in Musculoskeletal Radiology
15. Algorithms for classification of sequences and segmentation of prostate gland: an external validation study
    Xuemei Yin, Kexin Wang, Liang Wang, Zhenghan Yang, Yaofeng Zhang, Pengsheng Wu, Chenglin Zhao, Jun Zhang · 2024 · Abdominal Radiology
16. Cochrane corner: artificial intelligence for keratoconus
    Ethan Wen Wei Tiong, Su‐Hsun Liu, Darren Shu Jeng Ting · 2024 · Eye
17. Large language models (LLMs) in radiology exams for medical students: Performance and consequences
    Jennifer Gotta, Quang Anh Le Hong, Vitali Koch, Leon David Gruenewald, Tobias Geyer, Simon S. Martin, Jan‐Erik Scholtz, Christian Booz, Daniel Pinto dos Santos, Scherwin Mahmoudi et al. · 2024 · RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren
18. AI ‐Driven Detection and Measurement of Keratinized Gingiva in Dental Photographs: Validation Using Reference Retainers
    Ya‐Chi Chen, Ling Chen, Yu‐Lin Lai, Wei‐Ting Chang, Shyh‐Yuan Lee · 2025 · Journal Of Clinical Periodontology
19. Artificial Intelligence in bone Metastases: A systematic review in guideline adherence of 92 studies
    Lotte R van der Linden, Ioannis Vavliakis, Tom Maarten Groot, Paul C. Jutte, Job Nicolaas Doornberg, Santiago A. Lozano‐Calderón, Olivier Quinten Groot · 2025 · Journal of bone oncology
20. Artificial Intelligence-Assisted Segmentation of Prostate Tumors and Neurovascular Bundles: Applications in Precision Surgery for Prostate Cancer
    Haonan Mei, Rui Yang, Jun C. Huang, Panpan Jiao, Xiuheng Liu, Zhiyuan Chen, Hui Chen, Qingyuan Zheng · 2025 · Annals of Surgical Oncology
21. Interventional Radiology Reporting Standards and Checklist for Artificial Intelligence Research Evaluation (iCARE)
    James Anibal, Hannah B. Huth, Tom Boeken, Dania Daye, Judy Wawira Gichoya, Fernando Gómez, Julius Chapiro, Bradford J. Wood, Daniel Y. Sze, Klaus Armin Hausegger · 2025 · CardioVascular and Interventional Radiology
22. Early detection of pancreatic cancer on computed tomography: advancements with deep learning
    Felipe Lopez-Ramirez, Emir A. Syailendra, Florent Tixier, Satomi Kawamoto, Elliot K. Fishman, Linda Chi Hang Chu · 2025 · Radiology Advances
23. Transforming Intracerebral Hemorrhage Care with Artificial Intelligence: Opportunities, Challenges, and Future Directions
    Qian Gao, Yujia Jin, Yuxuan Sun, Meng Jin, Lili Tang, Yuxiao Chen, Yutong She, Meng Li · 2026 · Diagnostics
24. Basic principles of AI simplified for a Medical Practitioner: Pearls and Pitfalls in Evaluating AI algorithms
    Deeksha Bhalla, Anupama Ramachandran, Krithika Rangarajan, Rohan Raju Dhanakshirur, Subhashis Banerjee, Chetan Arora · 2022 · Current Problems in Diagnostic Radiology
25. Machine Learning Approaches to Identify Affected Brain Regions in Movement Disorders Using MRI Data: A Systematic Review and Diagnostic Meta‐analysis
    Sadegh Ghaderi, Mahdi Mohammadi, Fatemeh Sayehmiri, Sana Mohammadi, Arian Tavasol, Masoud Rezaei, Azadeh Ghalyanchi‐Langeroudi · 2024 · Journal of Magnetic Resonance Imaging
26. Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software
    Léa Ingrassia, Susana Boluda, Marie‐Claude Potier, Stéphane Haı̈k, Gabriel Jiménez, Anuradha Kar, Daniel Racoceanu, Benoı̂t Delatour, Lev Stimmer · 2024 · Journal of Neuropathology & Experimental Neurology
27. Performance of Commercial Deep Learning-Based Auto-Segmentation Software for Breast Cancer Radiation Therapy Planning: A Systematic Review
    Curtise K. C. Ng · 2024 · Multimodal Technologies and Interaction
28. Comparative Performance Evaluation of Multimodal Large Language Models, Radiologist, and Anatomist in Visual Neuroanatomy Questions
    Yasin Celal Güneş, Mehmet Ülkir · 2025 · Uludağ Üniversitesi Tıp Fakültesi Dergisi
29. Automated detection and classification of adrenal masses on CT using two annotation methods: Segmentation vs. bounding box
    Taku Takaishi, Yoshimasa Kokubo, K. Kondo, Kazuhisa Matsumoto, Tatsuhito Yamamoto, Shunsuke Shibata, Yusei Owatari, Fumito Nariyuki, Tatsuya Kawai, Akio Hiwatashi · 2025 · European Journal of Radiology Artificial Intelligence
30. Evaluating generative AI models for explainable pathological feature extraction in lung adenocarcinoma: grading assessment and prognostic model construction
    Junyi Shen, Suyin Feng, Zhenfa Zhang, Qi Chang, Zaoqu Liu, Yuying Feng, Chunrong Dong, Zhenyu Xie, Wenyi Gan, Lingxuan Zhu et al. · 2025 · International Journal of Surgery
31. Detection of lesions in the optic nerve with magnetic resonance imaging using a 3D convolutional neural network
    Gerard Martí‐Juan, Marcos Frías, Aran García-Vidal, Ángela Vidal‐Jordana, Manel Alberich, Willem Calderon, Gemma Piella, Óscar Cámara, Xavier Montalbán, Jaume Sastre‐Garriga et al. · 2022 · NeuroImage Clinical
32. The performance of machine learning approaches for attenuation correction of PET in neuroimaging: A meta-analysis
    Confidence Raymond, Michael Todd Jurkiewicz, Akintunde Taiwo Orunmuyi, Linshan Liu, Michael Oluwaseun Dada, Claes Nøhr Ladefoged, Jarmo Teuho, Udunna Anazodo · 2023 · Journal of Neuroradiology
33. Liver Transplant in Patients with Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence
    Mihai Dan Pomohaci, Mugur Cristian Grasu, Radu Lucian Dumitru, Mihai Toma, Ioana Gabriela Lupescu · 2023 · Diagnostics
34. Medical imaging: Challenges and future directions in AI-Based systems
    Rakesh Kumar, Mini Anil, Sampurna Panda, Ashish Raj · 2023 · AIP conference proceedings
35. A Regulatory Science Perspective on Performance Assessment of Machine Learning Algorithms in Imaging
    Wei-Jie Chen, Daniel M. Krainak, Berkman Sahiner, Nicholas Petrick · 2023 · Neuromethods
36. Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization
    Pedro Mateus, Leroy Volmer, Leonard Wee, Hugo J.W.L. Aerts, Frank J P Hoebers, Andre L.A.J. Dekker, Iñigo Bermejo · 2023 · Scientific Reports
37. Differentiation of COVID‐19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study
    Isaac Shiri, Yazdan Salimi, Abdollah Saberi, Masoumeh Pakbin, Ghasem Hajianfar, Atlas Haddadi Avval, Amirhossein Sanaat, Azadeh Akhavanallaf, Shayan Mostafaei, Zahra Mansouri et al. · 2024 · International Journal of Imaging Systems and Technology
38. MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis
    Karen Drukker, Berkman Sahiner, Tingting Hu, Grace Hyun J. Kim, Heather M. Whitney, Natalie M. Baughan, Kyle J. Myers, Maryellen Lissak Giger, Michael F. McNitt‐Gray · 2024 · Journal of medical imaging
39. Improving prediction of treatment response and prognosis in colorectal cancer with AI-based medical image analysis
    Xiangyu Liu, Song Zhang, Lizhi Shao, Caixia Sun, Bao Li, Wei Wei, Zuobin Ying, Zhenyu Liu, Jie Tian · 2024 · The Innovation Medicine
40. Limited capability of MRI radiomics to predict primary tumor histology of brain metastases in external validation
    Quirin Strotzer, Thomas Wagner, Pia Angstwurm, Katharina Hense, Lucca Scheuermeyer, Ekaterina Noeva, Johannes G. Dinkel, Christian Stroszczynski, Claudia Fellner, Markus J. Riemenschneider et al. · 2024 · Neuro-Oncology Advances
41. What's New in the Korean Journal of Radiology in 2021
    Seong Ho Park · 2020 · Korean Journal of Radiology
42. EVA: Valor Añadido Económico : un nuevo enfoque para optimizar la gestión, motivar y crear valor
    José Oriol Amat Salas · 1999 · Dialnet (Universidad de la Rioja)
43. Commentary: Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies
    Steve K. Joslyn, Josephine Faulkner, Doris Ma, Ryan B. Appleby · 2025 · Frontiers in Veterinary Science
44. Impact of intensity standardisation and ComBat batch size on clinical-radiomic prognostic models performance in a multi-centre study of patients with glioblastoma
    Kavi Fatania, Russell Thomas Frood, Hitesh B. Mistry, Susan C Short, James P.B. O’Connor, Andrew Frederick Scarsbrook, Stuart Currie · 2024 · European Radiology
45. Foundation Model and Radiomics-Based Quantitative Characterization of Perirenal Fat in Renal Cell Carcinoma Surgery
    Haonan Mei, Hui Chen, Qingyuan Zheng, Rui Yang, Nan Wang, Panpan Jiao, Xiao Wang, Zhiyuan Chen, Xiuheng Liu · 2025 · Academic Radiology
46. A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT
    Cong Zhang, Xin Gao, Xuebin Zheng, Jun Xie, Gang Ling Feng, Yunchao Bao, Pengfei Gu, Chuan He, Ruimin Wang, Jiahe Tian · 2025 · EJNMMI Research
47. Development and Validation an Integrated Deep Learning Model to Assist Eosinophilic Chronic Rhinosinusitis Diagnosis: A Multicenter Study
    Jingjing Li, Ning Mao, Surita Aodeng, Haicheng Zhang, Zhenzhen Zhu, Lei Wang, Yuzhuo Liu, Hang Qi, Hong Qiao, Yuxi Lin et al. · 2025 · International Forum of Allergy & Rhinology
48. AI demonstrates comparable diagnostic performance to radiologists in MRI detection of anterior cruciate ligament tears: a systematic review and meta-analysis
    Saran Singh Gill, Taha Haq, Yi Zhao, Mihailo Ristic, Dimitri Amiras, Chinmay Madhukar Gupte · 2025 · European Radiology
49. Critical Appraisal Tools for Evaluating Artificial Intelligence in Clinical Studies: Scoping Review
    Juan B Cabello, Vicente Ruiz García, Miguel Torralba, Miguel Maldonado Fernandez, Marimar Ubeda, Eukene Ansuategi, Luis Ramos-Ruperto, José Ignacio Emparanza, Iratxe Urreta, María Teresa Iglesias et al. · 2025 · Journal of Medical Internet Research
50. End-to-end CNN-based detection of permanent first molars and prediction of root development stages from panoramic radiographs
    Şükriye Türkoğlu Kayacı, Hamza Osman İlhan, Görkem Serbes, Hakan Arslan · 2025 · Scientific Reports
51. Artificial Intelligence and the Expanding Universe of Cardio-Oncology: Beyond Detection Toward Prediction and Prevention of Therapy-Related Cardiotoxicity—A Comprehensive Review
    Miruna Florina Ştefan, Stefania Lucia Magda, Dragoş Vinereanu · 2026 · Diagnostics
52. Surgical computer vision for intraoperative decision-support: a scoping review on performance metrics and readiness for real-time deployment
    Jayvee Buchanan, Saxon J. Connor, John F. Pearson, Bruce Carey-Smith, Tim Eglinton · 2026 · Artificial Intelligence Surgery
53. From Data to Decision: Standardization, Validation, and Regulatory Readiness of AI-Driven Analytical Chemistry Workflows
    Samah Abo El Abass, Abdulmalik S. A. Altamimi, Taibah Aldakhil, Pintu Prajapati · 2026 · Critical Reviews in Analytical Chemistry
54. Need for Transparency and Clinical Interpretability in Hemorrhagic Stroke Artificial Intelligence Research: Promoting Effective Clinical Application
    Chae Young Lim, Beomseok Sohn, Minjung Seong, Eung Yeop Kim, Sung Tae Kim, So Yeon Won · 2024 · Yonsei Medical Journal
55. Using artificial intelligence for bladder cancer detection during cystoscopy and its impact on clinical outcomes: a protocol for a systematic review and meta-analysis
    Mohamed Baana, Murtada Arkwazi, Yi Zhao, Ojone Ofagbor, Gaurika Bhardwaj, Mariam Lami, Eva M. Bolton, Rakesh Heer · 2024 · BMJ Open
56. Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs
    Ariana Familiar, Neda Khalili, Nastaran Khalili, Cassidy Schuman, Evan Grove, Karthik Viswanathan, Jakob Seidlitz, Aaron F. Alexander‐Bloch, Anna Zapaishchykova, Benjamin Harris Kann et al. · 2024 · American Journal of Neuroradiology
57. Convolutional neural networks for automatic MR classification of myocardial iron overload in thalassemia major patients
    Vincenzo Positano, Antonella Meloni, Lisa Anita De Santi, Laura Pistoia, Zelia Borsellino, Alberto Cossu, Francesco Massei, Paola Maria Grazia Sanna, Maria Filomena Santarelli, Filippo Cademartiri · 2024 · European Radiology
58. Deep learning for automated spinopelvic parameter measurement from radiographs: a meta-analysis
    D. Glaser, Ahmad Kareem Almekkawi, James P. Caruso, Candace Y. Chung, Eshal Z. Khan, Hicham M. Daadaa, Salah G. Aoun, Carlos A. Bagley · 2025 · Artificial Intelligence Surgery
59. Evolution of an Artificial Intelligence-Powered Application for Mammography
    Yuriy Aleksandrovich Vasilev, Румянцев Денис Андреевич, Anton V. Vladzymyrskyy, Olga V. Omelyanskaya, Пестренин Лев Дмитриевич, Шулькин Игорь Михайлович, Evgeniy D. Nikitin, Artem Kapninskiy, Kirill M. Arzamasov · 2025 · Diagnostics
60. Development and application of an intelligent platform for automated recognition of surgical instruments in laparoscopic procedures: a multicenter retrospective study (experimental studies)
    Ran Hu, Ming Tang, Yi Jin, Lelang Xiang, Keyu Li, Bing Peng, Jie Liu, Dian Qin, Liang Long, Yichuan Li et al. · 2025 · International Journal of Surgery
61. Best Practices and Checklist for Reviewing Artificial Intelligence-Based Medical Imaging Papers: Classification
    Timothy Lee Kline, Felipe Kitamura, Daniel Warren, Ian Pan, Amine Mohamed Korchi, Neil Tenenholtz, Linda P. Moy, Judy Wawira Gichoya, Igor Santos, Kamyar Moradi et al. · 2025 · Journal of Imaging Informatics in Medicine
62. Fully automated measurement of paediatric cerebral palsy pelvic radiographs with BoneFinder
    Katie Patterson Hughes, Jessenka Luzar, Jonathan Lang, Daniel C. Perry, Mark S. Gaston · 2025 · The Bone & Joint Journal
63. Improving Deep Neural Network Interpretation for Neuroimaging Using Multivariate Modeling
    Brady J. Williamson, David Wang, Vivek J. Khandwala, Jennifer Scheler, Achala S. Vagal · 2022 · SN Computer Science
64. An Interventional Radiologist’s Primer of Critical Appraisal of Artificial Intelligence Research
    Olivia Gaddum, Julius Chapiro · 2023 · Journal of Vascular and Interventional Radiology
65. 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. · 2023 · Nuklearmedizin - NuclearMedicine
66. Radiomic-based nonlinear supervised learning classifiers on non-contrast CT to predict functional prognosis in patients with spontaneous intracerebral hematoma
    E. Serrano, Javier Moreno, Laura Llull, Alejandro H. Rodríguez, Christian Zwanzger, Sergio Amaro, Laura Oleaga, Antonio López‐Rueda · 2023 · Radiología (English Edition)
67. “KAIZEN” method realizing implementation of deep-learning models for COVID-19 CT diagnosis in real world hospitals
    Naoki Okada, Yutaka Umemura, Shoi Shi, Shusuke Inoue, Shun Honda, Yohsuke Matsuzawa, Yuichiro Hirano, Ayano Kikuyama, Miho Yoshida Yamakawa, Tomoko Gyobu et al. · 2024 · Scientific Reports
68. Open science perspectives on machine learning for the identification of careless responding: A new hope or phantom menace?
    Andreas Alfons, Max Welz · 2024 · Social and Personality Psychology Compass
69. Deep learning to support the detection and classification of teeth, dental caries and restorations: a review
    José Andery Carneiro, Breno Augusto Guerra Zancan, Camila Tirapelli, Alessandra Alaniz Macedo · 2024 · Brazilian Journal of Health Review
70. Post-radiotherapy stage III/IV non-small cell lung cancer radiomics research: a systematic review and comparison of CLEAR and RQS frameworks
    Kevin Tran, Daniel Ginzburg, Wei Hong, Ulrike Irmgard Attenberger, Hyun Soo Ko · 2024 · European Radiology
71. A systematic review of deep learning-based spinal bone lesion detection in medical images
    Bianca Teodorescu, Leonard Gilberg, Philip William Melton, Rudolph Matthias Hehr, Hamza Eren Güzel, Ali Murat Koç, Andre Baumgart, Leander Maerkisch, Elmer Jeto Gomes Ataide · 2024 · Acta Radiologica
72. Generation of short-term follow-up chest CT images using a latent diffusion model in COVID-19
    Naoko Kawata, Yuma Iwao, Yukiko Matsuura, Takashi Higashide, Takayuki Okamoto, Yuki Sekiguchi, Masaru Nagayoshi, Yasuo Takiguchi, Takuji Suzuki, Hideaki Haneishi · 2024 · Japanese Journal of Radiology
73. Development of a deep learning-based model to evaluate changes during radiotherapy using cervical cancer digital pathology
    Masaaki Goto, Yasunori Futamura, Hirokazu Makishima, Takashi Kei SAITO, Noriaki Sakamoto, Tatsuo Iijima, YOSHIO TAMAKI, Toshiyuki Okumura, Tetsuya Sakurai, Hideyuki Sakurai · 2025 · Journal of Radiation Research
74. Artificial intelligence and its potential integration with the clinical practice of diagnostic imaging medical physicists: a review
    Ngo Fung Daniel Lam, Jing Cai, Kwan Hoong Ng · 2025 · Physical and Engineering Sciences in Medicine
75. Methodologic Assessment of a Deep Learning Approach Measuring Lung Opacification in COVID-19 at Chest CT
    Marcelo Straus Takahashi, Matheus R. F. Mendonça, Ian Pan, Rogério Zaia Pinetti, Felipe Kitamura · 2020 · Radiology Cardiothoracic Imaging
76. Deep Learning to Detect and Classify Teeth, Dental Caries and Restorations: A Systematic Mapping
    J. Carneiro, Breno Augusto Guerra Zancan, Camila Tirapelli, Alessandra Alaniz Macedo · 2023 · Research Square
77. Comparative analysis of transformer-based deep learning models for glioma and meningioma classification
    Katerina Nalentzi, Konstantinos Gerogiannis, Haralabos Bougias, Nikolaos Stogiannos, Periklis Papavasileiou · 2025 · Journal of medical imaging and radiation sciences
78. Clinical application of a deep learning system for automatic mandibular alveolar bone quantity assessment and suggested treatment options using CBCT cross-sections
    Mardin Othman Rashid, Shanaz Gaghor · 2025 · Medicine
79. High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach
    Juuso Takala, Heikki Peura, Riku Pirinen, Väätäinen Katri, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja · 2025 · Scientific Reports
80. Assessing deep learning artificial intelligence support for detecting elbow fractures in the pediatric emergency department
    Julie Da Costa, Bénédicte Vrignaud, Éric Frampas, Cyrille Decante, Laura Meurice, Karine Levieux, Christèle Gras‐Le Guen, Fleur Lorton · 2025 · European Journal of Radiology
81. Evaluating methodological quality in radiomics research using large language models: Added value of METRICS-E3 framework
    İsmail Meşe, Burak Koçak · 2025 · European Journal of Radiology
82. Keeping AI in medicine and radiology within the framework of scientific method: measuring to close the epistemic gap
    Filippo Pesapane, Francesco Sardanelli · 2025 · Insights into Imaging
83. Predicting the Value of Radiology Artificial Intelligence Applications: Large-Scale Predeployment Evaluation of a Portfolio of Models
    David B. Larson, Jason A. Poff, Sriyesh Krishnan, Jerome Avondo, Bonnie Andrea Armstrong, Hye Sun Na, Akshay Sanjay Chaudhari, Nina E. Kottler · 2026 · American Journal of Roentgenology
84. Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging
    Paolo Simoni, Mariantonietta Francavilla, Patrick Omoumi, Maria Pilar Aparisi Gómez, Chiara Giraudo, Grammatina Boitsios · 2026 · Pediatric Radiology
85. Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial
    Santiago Cepeda, Elena Hernando-Pérez, Enrique Pérez-Riesgo, Isabel Rodríguez-Valle, O Esteban Sinovas, Ignacio Arrese, María Miguel Lucero- Salaverry, Tomás Zamora, María Ángeles Torres-Nieto, Luigi Tommaso Luppino et al. · 2026 · Neuro-Oncology
86. Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data
    Blair Edward Warren, Fahd Alkhalifah, Aida Ahrari, Adam Min, Aly Fawzy, Ganesan Annamalai, Arash Jaberi, Rob Beecroft, John R. Kachura, Sebastian Charles Mafeld · 2024 · Canadian Association of Radiologists Journal
87. Human-in-the-Loop—A Deep Learning Strategy in Combination with a Patient-Specific Gaussian Mixture Model Leads to the Fast Characterization of Volumetric Ground-Glass Opacity and Consolidation in the Computed Tomography Scans of COVID-19 Patients
    Constanza Vásquez-Venegas, Camilo G. Sotomayor, Baltasar Ramos, Víctor Castañeda, Gonzalo Pereira, G. Cabrera-Vives, Steffen Härtel · 2024 · Journal of Clinical Medicine
88. Artificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture: a critical review
    Robert Miller, Laurence H. Jackson, Dijana Vilić, Louis Boyce, Haris Shuaib · 2025 · Journal of Hand Surgery (European Volume)
89. Interventional Radiology Reporting Standards and Checklist for Artificial Intelligence Research Evaluation (iCARE)
    James Anibal, Hannah B. Huth, Tom Boeken, Dania Daye, Judy Wawira Gichoya, Fernando Gómez, Julius Chapiro, Bradford J. Wood, Daniel Y. Sze, Klaus Armin Hausegger · 2025 · Journal of Vascular and Interventional Radiology
90. Linking Symptom Inventories Using Semantic Textual Similarity
    Eamonn Kennedy, Shashank Vadlamani, Hannah Michelle Lindsey, Kelly Peterson, Kristen Dams-O’Connor, Ronak Agarwal, Houshang Amiri, Raeda K. Andersen, Talin Babikian, David A. Baron et al. · 2025 · Journal of Neurotrauma
91. Quantitative Ischemic Lesions of Portable Low–Field Strength MRI Using Deep Learning–Based Super-Resolution
    Yueyan Bian, L. Wang, Jin Li, Xiaoxu Yang, Erling Wang, Yingying Li, Yuehong Liu, Lei Xiang, Qi Yang · 2025 · Stroke
92. Diagnosis of sacroiliitis using MR images with a simplified custom deep learning model
    Uzelaltinbulat, Selin, Kucukciloglu, Yasemin, Ilhan, Ahmet, Mirzaei, Omid, Sekeroglu, Boran · 2025 · The Journal of Supercomputing
93. Empowering the future of spinal surgery through digital and intelligent technologies
    Chenfei Gao, Tianyu Yao, Tenghui Zhang, Wenyu Zhang, Jianxi Wang, Fazhi Zang, Huajiang Chen · 2025 · Spine Research
94. The Use of Artificial Intelligence in Urologic Oncology: Current Insights and Challenges
    Rossella Cicchetti, Daniele Amparore, Flavia Tamborino, Octavian Sabin Tătaru, Matteo Ferro, Alessio Digiacomo, Giulio Litterio, Angelo Orsini, Salvatore Granata, Riccardo Campi et al. · 2025 · Research and Reports in Urology
95. Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy
    Valentina Bellini, Francesco Calabrò, Elena Giovanna Bignami, Tudor Mihai Haja, Iben Fasterholdt, Benjamin Schnack Rasmussen, Rossana Cecchi · 2025 · Journal of Medical Systems
96. An Explainable Deep Learning Model for Focal Liver Lesion Diagnosis Using Multiparametric MRI
    Zhehan Shen, Lingzhi Chen, Lilong Wang, Shunjie Dong, Fakai Wang, Yaning Pan, Jiahao Zhou, Yikun Wang, Xinxin Xu, Huanhuan Chong et al. · 2025 · Radiology Artificial Intelligence
97. Artificial Intelligence–Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study
    Ansaar Rai, Abdulrahman Al Halak, Mohamad K. Abdalkader, Artem Kaliaev, Thanh Ngoc Nguyen, David F. Kallmes, Waleed Brinjikji, Thien J Huynh, Dhairya A. Lakhani, Alistair Perry et al. · 2025 · American Journal of Neuroradiology
98. Liver Segment and Lesion Segmentation on CT and MRI: An Open-Source Contribution to TotalSegmentator
    Andrew Phillip Nicoli, Michael Bach, Jakob Wasserthal, Ashraya Kumar Indrakanti, Martin Segeroth, Shan Yang, Joshy Cyriac, Daniel Tobias Boll, Adrian Jonathan Wilder-Smith · 2025 · Journal of Imaging Informatics in Medicine
99. Enhancing reproducibility of machine learning‐based studies in clinical journals through model cards
    Jonathan Dan, Nick Seeuws · 2023 · Developmental Medicine & Child Neurology
100. Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT images
     Robert O’Shea, Carolyn Horst, Thubeena Manickavasagar, Daniel Johnathan Hughes, James Cusack, Sophia Tsoka, Gary Cook, Vicky Goh · 2023 · Insights into Imaging