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

Cited by (1,001)

Items 801–900 of 1,001

1. Automatic segmentation of fat metaplasia on sacroiliac joint MRI using deep learning
   Xin Li, Yi Lin, Zhuoyao Xie, Zixiao Lu, Liwen Song, Qiang Ye, Menghong Wang, Xiao Fang, Yi He, Hao Chen et al. · 2024 · Insights into Imaging
2. Artificial intelligence in diagnosis of prostate cancer using magnetic resonance imaging. New approach
   I. A. Aboyan, Vladimir Redkin, M. G. Nazaruk, Andrey S. Polyakov, S. M. Pakus, S. I. Lemeshko, Alan Hasigov · 2024 · Cancer Urology
3. Development and validation of deep learning models for bowel obstruction on plain abdominal radiograph
   Yao Li, Shiqi Zhu, Yu Wang, Bowei Mao, Jielu Zhou, Jinzhou Zhu, Chenqi Gu · 2024 · Journal of International Medical Research
4. Segmentation-Free Estimation of Left Ventricular Ejection Fraction Using 3D CNN Is Reliable and Improves as Multiple Cardiac MRI Cine Orientations Are Combined
   Philippe Germain, Aïssam Labani, Armine Vardazaryan, Nicolas Padoy, Catherine Roy, Soraya El Ghannudi · 2024 · Biomedicines
5. Breast radiotherapy planning: A decision‐making framework using deep learning
   Pedro Gallego, Eva Ambroa, Jaime Perez-Alija, N. Jornet, Cristina Anson, Natalia Tejedor, Helena Vivancos, A. Castillo Ruiz, Marta Barceló, Alejandro Domínguez et al. · 2024 · Medical Physics
6. Deep learning enhanced transmembranous electromyography in the diagnosis of sleep apnea
   Ross M. Mandeville, Hooman Sedghamiz, Perry T. Mansfield, Geoffrey L. Sheean, Chris Studer, Derrick Cordice, Ghodsieh Ghanbari, Atul Malhotra, Shamim Nemati, Jejo Koola · 2024 · BMC Neuroscience
7. Checklist and reporting framework to support documentation and communication of GIS-based Multi-Criteria Evaluation (MCE) models for aquaculture site selection
   Megan Silverthorn, Suleiman O. Yakubu, Lynne Falconer · 2025 · PLOS Sustainability and Transformation
8. Multivariable prognostic models for post-hepatectomy liver failure: An updated systematic review
   Xiao Wang, Ming-Xiang Zhu, Junfeng Wang, Pan Liu, Li-Yuan Zhang, You Zhou, Xi-Xiang Lin, Yong Du, Kunlun He · 2025 · World Journal of Hepatology
9. Integration of magnetic resonance imaging and deep learning for prostate cancer detection: a systematic review
   Deepak Kumar · 2025 · American Journal of Clinical and Experimental Urology
10. Automated Identification of Multiple Findings on Brain MRI for Improving Scan Acquisition and Interpretation Workflows: A Systematic Review
    Kaining Sheng, Cecilie Mørck Offersen, Jon Middleton, Jonathan Frederik Carlsen, Thomas Clement Truelsen, Akshay Pai, Jacob Johansen, Michael Bachmann Nielsen · 2022 · Diagnostics
11. Application of A U-Net for Map-like Segmentation and Classification of Discontinuous Fibrosis Distribution in Gd-EOB-DTPA-Enhanced Liver MRI
    Quirin Strotzer, Hinrich Boy Winther, Kirsten Utpatel, Alexander Scheiter, Claudia Fellner, Michael Christian Doppler, Kristina Imeen Ringe, Florian Raab, Michael Haimerl, Wibke Uller et al. · 2022 · Diagnostics
12. The application of machine learning to imaging in hematological oncology: A scoping review
    Stylianos Kotsyfakis, Evangelia Iliaki-Giannakoudaki, Antonios Anagnostopoulos, Eleni Papadokostaki, Konstantinos Giannakoudakis, Michail Goumenakis, Michail Kotsyfakis · 2022 · Frontiers in Oncology
13. Introducing Computer Vision into Healthcare Workflows
    Candelaria Mosquera, María Agustina Ricci Lara, Facundo Nahuel Díaz, Fernando Binder, Sonia Benítez · 2023 · Health informatics
14. Toward Real-World Computational Nephropathology
    Rodrigo Tripodi Calumby, Angelo Amâncio Duarte, Michele Fúlvia Ângelo, Emanuele Santos, Pinaki Sarder, Washington L. C. dos‐Santos, Luciano Rebouças de Oliveira · 2023 · Clinical Journal of the American Society of Nephrology
15. Using deep learning–derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data
    Brendan S. Kelly, Prateek Mathur, Jan Plesniar, Aonghus Lawlor, Ronan P. Killeen · 2023 · European Radiology
16. A systematic review of radiomics in giant cell tumor of bone (GCTB): the potential of analysis on individual radiomics feature for identifying genuine promising imaging biomarkers
    Jingyu Zhong, Yue Xing, Guangcheng Zhang, Yangfan Hu, Defang Ding, Xiang Ge, Zhen Pan, Qian Yin, Huizhen Zhang, Qingcheng Yang et al. · 2023 · Journal of Orthopaedic Surgery and Research
17. Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases
    Lorenzo Storino Ramacciotti, Jacob S. Hershenhouse, Daniel Mokhtar, Divyangi Paralkar, Masatomo Kaneko, Michael Eppler, Karanvir S. Gill, Vasileios Mogoulianitis, Vinay Anant Duddalwar, Andre Luis Abreu et al. · 2023 · Urologic Clinics of North America
18. Clasificadores de aprendizaje supervisado no lineales basados en radiómica de la TC cerebral sin contraste para predecir el pronóstico funcional en pacientes con hematoma intracerebral espontáneo
    E. Serrano, Javier Moreno, Laura Llull, Alejandro H. Rodríguez, Christian Zwanzger, Sergio Amaro, Laura Oleaga, Antonio López‐Rueda · 2023 · Radiología
19. Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review
    Jeffrey H. Maki, Nayana U. Patel, Ethan J. Ulrich, Jasser Dhaouadi, Randall W. Jones · 2024 · Current Problems in Diagnostic Radiology
20. Adherence of studies involving artificial intelligence in the analysis of ophthalmology electronic medical records to AI-specific items from the CONSORT-AI guideline: a systematic review
    Niveditha Pattathil, Tin-Suet Joan Lee, Ryan S. Huang, Eleanor R. Lena, Tina Felfeli · 2024 · Graefe s Archive for Clinical and Experimental Ophthalmology
21. Deep learning convolutional neural network (DLCNN): unleashing the potential of 18F-FDG PET/CT in lymphoma.
    Ke Li, Ran Zhang, Weibo Cai · 2021 · PubMed Central
22. 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 · 2022
23. Automated artificial intelligence scoring systems for the endoscopic assessment of ulcerative colitis: How far are we from clinical application?
    Alberto Murino, Alessandro Rimondi · 2022 · Gastrointestinal Endoscopy
24. Deep learning–based diagnostic models for bone lesions: is current research ready for clinical translation?
    Jingyu Zhong · 2024 · European Radiology
25. Preparing Radiologists for an Artificial Intelligence–enhanced Future: Tips for Trainees
    Pouria Rouzrokh, Jamie E. Clarke, Melina Hosseiny, Moozhan Nikpanah, Mahati Mokkarala · 2024 · Radiographics
26. In Silico Evaluation of Algorithm-Based Clinical Decision Support Systems: Protocol for a Scoping Review
    Michael Dorosan, Ya-Lin Chen, Qingyuan Zhuang, Shao Wei Lam · 2024 · JMIR Research Protocols
27. Clinical Application of Deep Learning-Assisted Needles Reconstruction in Prostate Ultrasound Brachytherapy
    Mathieu Goulet, Patricia Duguay‐Drouin, Julia Mascolo‐Fortin, Julien Mégrourèche, Nadia Octave, James Man Git Tsui · 2025 · International Journal of Radiation Oncology*Biology*Physics
28. Ovarian masses suggested for MRI examination: assessment of deep learning models based on non-contrast-enhanced MRI sequences for predicting malignancy
    Meijiao Jiang, Chui Kong, Siwei Lu, Qingwan Li, Caiting Chu, Wenhua Li · 2025 · Abdominal Radiology
29. D2-RD-UNet: A dual-stage dual-class framework with connectivity correction for hepatic vessels segmentation
    Matteo Cavicchioli, Andrea Moglia, Guillaume Garret, Martina Puglia, Antoine Vacavant, Giacomo Pugliese, Pietro Cerveri · 2025 · Computers in Biology and Medicine
30. Neurodegenerative Disease Classification with EEG: A Deep Learning Approach for Dementia Diagnosis
    Ανδρέας Μιλτιάδους, Konstantinos Sakkas, Emmanouil D. Oikonomou, Aimilia Ntetska, Νικόλαος Γιαννακέας, Alexandros T. Tzallas · 2025 · Proceedings - IEEE Symposium on Computer-Based Medical Systems
31. Machine Learning to Predict Extranodal Extension in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta‐Analysis
    Arshbir Aulakh, Masih Sarafan, Amardeep Singh Sekhon, Khanh Linh Tran, Ameen Amanian, Farahna Sabiq, Cornelius H. L. Kürten, Eitan Prisman · 2025 · The Laryngoscope
32. A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction Using Deep Learning
    Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou, Dimitrios J. Apostolopoulos · 2025 · Applied Sciences
33. Deep learning models for segmentation and quantification of left atrial appendage volume using noncontrast cardiac computed tomography
    Daniel Augusto Message Santos, Lucas de Oliveira Teixeira, Miyoko Massago, Sérgio Silva, Sanderland José Tavares Gurgel, Carlos Eduardo Rochitte, Yandre M. G. Costa, Luciano de Andrade · 2025 · Journal of Cardiovascular Imaging
34. Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography
    Graziella Di Grezia, Antonio Nazzaro, Elisa Cisternino, Alessandro Galiano, Luca Marinelli, Sara Mercogliano, Vincenzo Cuccurullo, Gianluca Gatta · 2025 · Diagnostics
35. Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy
    Kalab Yigermal Gete, Asnakew Achaw Ayele · 2025 · BMC Neurology
36. Evaluating Generative Artificial Intelligence as an Educational Tool for Radiology Resident Report Drafting
    Antonio Verdone, Aidan Cardall, Fardeen A. Siddiqui, Motaz Nashawaty, Danielle N. Rigau, Young Joon Kwon, Mira Yousef, Shalin Patel, Alexander J. Kieturakis, Eric Kim et al. · 2025 · Journal of the American College of Radiology
37. Deep Learning–Based Segmentation of Coronary Arteries and Stenosis Detection in X-Ray Coronary Angiography
    Mitchel A. Molenaar, Elsa Hebbo, Jasper L. Selder, Nikoloz Shekiladze, Pratik B. Sandesara, William J. Nicholson, Folkert Wouter Asselbergs, Syed Arif Ahmad, Daniel A. Gold, Shaimaa M. Sakr et al. · 2025 · JACC Advances
38. Potential change in healthcare costs of implementing artificial intelligence for detecting cervical spine fractures on CT: an early health technology assessment
    Gaby J. van den Wittenboer, Ingrid M. Nijholt, Ingelin Kvamme, Chris van Lieshout, Mario M. Maas, Martijn F. Boomsma · 2026 · European Radiology
39. Personalized Medicine Through AI-Driven Imaging
    Rohit Ramesh Doke, Jeevan R. Rajguru, Kuldeep Vinchurkar · 2026 · Springer eBooks
40. Mapping the Scientific Landscape of Artificial Intelligence in Endodontics: A Bibliometric Analysis
    Ekin Deniz Çatmabacak, Ahmet Kerem Eren, İrem Çetinkaya · 2026 · International Endodontic Journal
41. Artificial intelligence in virtual fracture clinics: a systematic review of imaging and clinical-text tools
    Tenghis Sukhbaatar, Andrew Davies, Aran Koye, Mohamed Hashem, Sivan S. Sivaloganathan · 2026 · Journal of Orthopaedic Surgery and Research
42. Beyond handcrafted radiomics in oncologic imaging: Innovations in deep, explainable, multi-site and multi-omics radiomics approaches
    Jules Dupont, Fiona Frau, Victor Robic, Marina Manso Jimeno, Letuan Phan, Stéphanie Nougaret, Samy Ammari, Paul-Henry Cournède, Antoîne Italiano, Nathalie Lassau et al. · 2026 · Diagnostic and Interventional Imaging
43. Automated Identification of Accessory Mental Foramen Using Cone-Beam Computed Tomography and Convolutional Neural Networks
    Zuhal Ovuz, Eda GÜRSU ŞAHİN, Taha Etem · 2026 · International Dental Journal
44. AID-RT: Standardising Artificial Intelligence Documentation in RadioTherapy with a domain-specific model card
    Ana María Barragán Montero, Margerie Huet‐Dastarac, Silvia M. Herranz-Hernández, Benjamin Tengler, Emma Skarsø Buhl, Arthur Galapon, Carlos E. S. Cárdenas, Marco Fusella, Geoffroy Herbin, Yvonne J M de Hond et al. · 2026 · Physics and Imaging in Radiation Oncology
45. Transparent reporting is central to reproducible radiological AI research: A call to action
    Samuel J. White, Kaspar L. Yaxley, Minh‐Son To, Minh Toan Chau · 2026 · European Journal of Radiology
46. Radiographic choice for skeletal maturation assessment: a systematic review of Cervical Vertebrae Method and Middle Phalanx Method
    Angelo Michele Inchingolo, Grazia Marinelli, Francesca Calò, Claudia Ciocia, Antonio Rizzo, Francesco Inchingolo, Gianluca Martino Tartaglia, Massimo DEL FABBRO, Andrea Palermo, Daniela Di Venere et al. · 2026 · Oral Radiology
47. Diagnostic assessment of artificial intelligence reconstruction on accelerated prostate MRI: a retrospective, paired, multi-reader multi-case study
    Quintin van Lohuizen, Stefan Johannes Fransen, George Yiasemis, Jasper J. Twilt, Christian Roest, Yuki Arita, Jacob Borstlap, Jurgen J. Fütterer, Maarten de Rooij, Dennis B. Rouw et al. · 2026 · European Radiology
48. AI in Oral Health Surveillance: Critical Review
    Z. Chen, P. Liu, Kai Han, Peixi Liao, Y. Yang, MCM Wong, Cynthia Kar Yung Yiu, E.C.M. Lo · 2026 · Journal of Dental Research
49. Are AI Neuroimaging Models Ready for Clinical Use? A Systematic Methodological Review
    Umid Sulaimanov, Nafiye Şanlıer, Ariorad Moniri, Behman Demir, Y.S. Serikkanov, Ahmed Rasim BAYRAMOĞLU, Maryam Sabah Al-Jebur, Irem Uslu, Oyku Ozturk, Mariagrazia Nizzola et al. · 2026 · Journal of Clinical Medicine
50. Diagnostic performance of artificial intelligence in periapical radiography: a systematic review
    Tülin Taşdemir, Melek Taşsöker, Abdullah Arpacı, Ayşenur Kula, Ferhat Enes Kocabiyik, Mehmet Enes İyişenyürek, Hüseyin Haklı · 2026 · Odontology
51. Interpretable MRI-based Multiparametric Radiomics for Preoperative Prediction of CMS4 Colorectal Cancer
    Zonglin Liu, Wenchao Gu, Liheng Liu, Shiman Wu, Zhenwei Yao, Yiqun Sun, Dan Huang, Tong Tong · 2026 · Radiology
52. Machine Learning for Clinical Electrophysiology
    Axel Loewe, Giorgio Luongo, Jorge Sánchez · 2022 · Lecture notes in bioengineering
53. Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs
    Jae‐Yeon Hwang, Yisak Kim, Jisun Hwang, Yehyun Suh, Sook Min Hwang, Hyeyun Lee, Minsu Park · 2024 · Pediatric Radiology
54. Clinical application of machine-based deep learning in patients with radiologically presumed adult-type diffuse glioma grades 2 or 3
    Tomás Gómez Vecchio, Alice Neimantaite, Erik Thurin, Julia Furtner, Ole Skeidsvoll Solheim, Johan Pallud, Mitchel Stuart Berger, Georg Widhalm, Jiri Jr Bartek, Ida Häggström et al. · 2024 · Neuro-Oncology Advances
55. Enhancing mortality prediction in patients with spontaneous intracerebral hemorrhage: Radiomics and supervised machine learning on non-contrast computed tomography
    Antonio López‐Rueda, María-Ángeles Rodríguez-Sánchez, Elena Serrano, Javier Moreno, Alejandro H. Rodríguez, Laura Llull, Sergio Amaro, Laura Oleaga · 2024 · European Journal of Radiology Open
56. AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review
    Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala · 2025 · Diagnostics
57. Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning
    Liang Wang, Peipei Zhang, Yanhui Feng, Wenzhi Lv, Xiangde Min, Zhiyong Liu, Jin Li, Zhaoyan Feng · 2025 · BMC Cancer
58. Artificial Intelligence in Radiology: Performance of ChatGPT-4v and GPT-4o on Diagnostic Radiology in-Training (DXIT) Examination Questions
    Reema Martini, Alan Sang, Pedro Saunders, Wasif Bala, Hanzhou Li, John T. Moon, Patricia Balthazar · 2025 · Journal of the American College of Radiology
59. Clinical Machine Learning Modeling Studies: Methodology and Data Reporting
    Oana Dumitrașcu, Yalin Wang, John Jing-Wei Chen · 2022 · Journal of Neuro-Ophthalmology
60. Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey
    Rui Li, Vaibhav Sharma, Subasini Thangamani, Artur Yakimovich · 2022 · Frontiers in Bioinformatics
61. Opportunities and Challenges for Deep Learning in Brain Lesions
    Jay Patel, Ken Chang, Syed Rakin Ahmed, Ikbeom Jang, Jayashree Kalpathy–Cramer · 2022 · Lecture notes in computer science
62. Sex, ethnicity, and race data are often unreported in artificial intelligence and machine learning studies in medicine
    Mahmoud Elmahdy, Ronnie Sebro · 2023 · Intelligence-Based Medicine
63. A head-to-head comparison of computed tomography- and magnetic resonance imaging-based radiomics in assessing pediatric peripheral neuroblastic tumor cell behavior
    Haoru Wang, Xin Chen, Ling He, Hao Ding, Mingye Xie, Jinhua Cai · 2024 · Abdominal Radiology
64. Radiomics-Based Differentiation of Glioblastoma and Metastatic Disease: Impact of Different T1-Contrast-Enhanced Sequences on Radiomics Features and Model Performance
    Girish Bathla, Camila Gadens Zamboni, Nicholas Bradley Larson, Yanan Liu, Honghai Zhang, Nam H. Le, Amit Kumar Agarwal, Neetu Soni, Milan Sonka A · 2024 · American Journal of Neuroradiology
65. Risk and Uncertainty Communication in Deployed AI-based Clinical Decision Support Systems: A scoping review
    Nicholas Gray, H. Page, I. Buchan, D. Joyce · 2024 · medRxiv
66. Research in Musculoskeletal Radiology: Setting Goals and Strategic Directions
    Michail E. Klontzas, Apostolos H. Karantanas · 2022 · Seminars in Musculoskeletal Radiology
67. Radiologist vs Machine Learning: A Comparison of Performance in Cancer Imaging
    Destie Provenzano, Yuan James Rao, Sharad Goyal, Shawn Haji-Momenian, John P. Lichtenberger, Murray H. Loew · 2021 · IEEE Applied Imagery Pattern Recognition Workshop
68. Using Radiomics to Differentiate Bone Islands versus Osteoblastic Bone Metastases at Abdominal CT
    Michael Walter Vannier · 2021 · Radiology
69. RSNA-MICCAI Panel Discussion: 2. Leveraging the Full Potential of AI—Radiologists and Data Scientists Working Together
    Marius George Linguraru, Lena Maier‐Hein, Ronald M. Summers, Charles E. Kahn · 2021 · Radiology Artificial Intelligence
70. Deep Learning Algorithms for Detecting Acute Thoracic Aortic Dissection on Plain Chest Radiography: A Retrospective Multicenter Study
    Dongkeon Lee, Jin Hyuk Kim, Jaehoon Oh, Tae Hyun Kim, Myeong Seong Yoon, Dong Jin Im, Jae Ho Chung, Hayoung Byun · 2022 · Research Square
71. Editorial for “Deep‐Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi‐Parametric MRI ”
    Barış Türkbey · 2023 · Journal of Magnetic Resonance Imaging
72. Towards Responsible Artificial Intelligence in Medicine: Reflections from the Australian Epilepsy Project
    Mangor Pedersen, Heath Pardoe, Anton de Weger, Donna M. Hutchison, David Abbott, Karin M. Verspoor, Graeme D. Jackson · 2023
73. A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data
    Anna Breger, IAN A. SELBY, Michael T. Roberts, Judith L Babar, Effrossyni Gkrania‐Klotsas, Jacobus Preller, Lorena Escudero Sánchez, Sören Dittmer, Matthew Thorpe, Julian Gilbey et al. · 2023 · Scientific Data
74. Human intelligence for authors, reviewers and editors using artificial intelligence
    Mauricio Palacios · 2023 · Colombia medica
75. Human-centered Evaluation of AI and ML Projects
    Yury Rusinovich, Alexander Vareiko, Nikita Shestak · 2024 · Web3 Journal ML in Health Science
76. No-code machine learning in radiology: implementation and validation of a platform that allows clinicians to train their own models
    Daniel C. Elton, Giridhar Dasegowda, Jefferson Koji Sato, Emiliano Garza-Frias, Christopher P. Bridge, Artem B. Mamonov, Mark Walters, Martynas Ziemelis, Thomas J. Schultz, Bernardo Canedo Bizzo et al. · 2024 · medRxiv
77. Explainable machine-learning model to classify culprit calcified carotid plaque in embolic stroke of undetermined source
    Yu Sakai, Jiehyun Kim, Huy Q. Phi, Andrew C Hu, Pargol Balali, Konstanze Viktoria Guggenberger, John H. Woo, Daniël Bos, Scott Eric Kasner, Brett L. Cucchiara et al. · 2024 · medRxiv
78. Artificial intelligence in ultrasound imaging: Inevitable, promising, and in need of responsible stewardship
    Manjiri Dighe · 2026 · WFUMB Ultrasound Open
79. The role of deep learning in aortic aneurysm segmentation and detection from CT scans: A systematic review and meta-analysis
    Tingwei Wang, Yun-Hsuan Tzeng, Jia‐Sheng Hong, Ho-Ren Liu, Hao-Neng Fu, Yung‐Tsai Lee, Wei‐Hsian Yin, Yu‐Te Wu · 2024 · Next research.
80. TAOD-Net: Automated detection and analysis of thyroid-associated orbitopathy in facial imagery
    YongKyung Oh, Giheon Koh, Jiin Kwak, Kyubo Shin, Gi-Soo Kim, Min Joung Lee, Ho-Kyung Choung, Sungil Kim, Jae Hoon Moon, Sungil Kim · 2025 · Computers & Industrial Engineering
81. Fully Automatic Artificial Intelligence Liver Anatomy Segmentation in the Management of Colorectal Liver Metastases
    Andrea Piero Chierici, Lisa Guzzi, Sébastien Goffart, Nizar Kamoun, Manuel Gargiulo, P. Chevallier, Antonio Iannelli, Rodolphe Anty, Hervé Delingette, Fabien Lareyre et al. · 2025 · Cureus
82. Development and validation of an AI-driven radiomics model using non-enhanced CT for automated severity grading in chronic pancreatitis
    Chengwei Chen, Jian Zhou, Shaojia Mo, Jing Li, Xu Fang, Fang Liu, Tiegong Wang, Li Wang, Jianping Lu, Chengwei Shao et al. · 2025 · European Radiology
83. Developing a Criteria Framework for Peer Review: A Critical Interpretive Synthesis
    Yifei Li, Xiaoting Xu, Dongqing Lyu, Zhen Zhang, Juan Xie, Ying Cheng · 2025 · Learned Publishing
84. Multi-Cohort Federated Learning Shows Synergy in Mortality Prediction for MRI-Based and Metabolomics-Based Age Scores
    Pedro Mateus, Swier J.F. Garst, Jing Yu, Davy Cats, Alexander G. J. Harms, Mahlet A. Birhanu, Marian Beekman, P. Eline Slagboom, Marcel J. T. Reinders, Jeroen van der Grond et al. · 2025 · Journal of Healthcare Informatics Research
85. Deep Learning Model for Osteoporosis Screening From Chest Radiographs: A Multicenter Analysis of External Robustness and Model Calibration
    Yuichi Imoto, Takahiro Inui, Kentaro Matsui, Yoshinobu Watanabe, Takashi Igari, Shu Takeuchi, Mana Kimura, Satoshi Yagi, Hirotaka Kawano · 2025 · Cureus
86. Development of a deep learning algorithm for radiographic detection of syndesmotic instability in ankle fractures with intraoperative validation
    Joshua Kubach, Tobias Pogarell, Michael Uder, Mario Perl, Marcel Betsch, Mario Pasurka, Stefan Söllner, Rafael U. Heiss · 2025 · Scientific Reports
87. Utilisation of artificial intelligence to enhance the detection rates of renal cancer on cross-sectional imaging: protocol for a systematic review and meta-analysis
    Ojone Ofagbor, Gaurika Bhardwaj, Yi Zhao, Mohamed Baana, Murtada Arkwazi, Mariam Lami, Eva M. Bolton, Rakesh Heer · 2025 · BMJ Open
88. Detecting papilloedema as a marker of raised intracranial pressure using artificial intelligence: A systematic review
    Lekaashree Rambabu, Thomas Edmiston, Brandon George Smith, Katharina Kohler, Angelos Georgiou Kolias, Richard A. I. Bethlehem, Pearse Andrew Keane, Hani Joseph Marcus, Peter J. Hutchinson, Tom Bashford · 2025 · PLOS Digital Health
89. Deep Learning Estimation of 24-2 Visual Field Map From Optic Nerve Head Optical Coherence Tomography Angiography
    Golnoush Mahmoudinezhad, Sasan Moghimi, Liyang Ru, Yu Xuan Yong, Dongchen Yang, Jiacheng Cheng, Siavash Beheshtaein, Evan Walker, Kareem Latif, Kelvin H. Du et al. · 2025 · Journal of Glaucoma
90. Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study
    Ching‐Yi Wu, Jia‐Da Li, Po-Yuan Shih, Cheng-Chia Huang, Hsiao‐Liang Cheng, Chun‐Yu Wu, Joyce Tay, Meng‐Che Wu, Chih‐Hung Wang, Chu‐Song Chen et al. · 2025 · Journal of Medical Systems
91. YOLOv5 Attention Analysis for Anterior Eye Disease Classification: Grad-CAM++ Feature Importance and Cut-and-Paste Validation
    Yoshiyuki Kitaguchi, Yuta Ueno, Takefumi Yamaguchi, Hiroki Maehara, Dai Miyazaki, Ryohei Nejima, Takenori Inomata, Naoko Kato, Tai-ichiro Chikama, Jun Ominato et al. · 2025 · Journal of Imaging Informatics in Medicine
92. Guidelines and Checklists for Artificial Intelligence (AI) in Surgical Education Research: A Comprehensive Narrative Review
    Caitlin J. Silvestri, Darian L Hoagland, John M. Woodward, Ariana Naaseh, Colleen E. McDermott, Brian M. Carter, Sarah B. Lund, Larry J. Prokop, Alec Bernard, Sergio Michael Navarro · 2025 · Journal of surgical education
93. Diagnostic accuracy of artificial intelligence-assisted radiology assessment of cancer: a systematic review
    Dylan Zhao, Thomas Packer, Xiaobo Jie, Muhammad Shahid, Jason Lee Oke, Annette Plüddemann · 2025 · BJR|Artificial Intelligence
94. Physics-aware imaging AI for quantitative MASLD biomarker mapping: a systematic review of deep learning and radiomics across ultrasound, CT, and MRI
    Houshyar Maghsoudi, Ahmad Khonche, Reza Gereami, Farshad Gharebakhshi · 2025 · Abdominal Radiology
95. From advanced imaging to molecular insights: the state of the art in omics for axial spondyloarthritis
    Iván Arias-de la Rosa, Jesús Eduardo Martín-Salazar, Laura Cuesta-López, Clementina López‐Medina, Alejandro Escudero-Contreras, Eduardo Collantes‐Estévez, Nuria Barbarroja, María Ángeles Puche-Larrubia · 2025 · Therapeutic Advances in Musculoskeletal Disease
96. Common Pitfalls and Recommendations for Use of Machine Learning in Depression Severity Estimation: DAIC-WOZ Study
    Ivan Danylenko, Olgierd Unold · 2025 · Applied Sciences
97. Evolving Paradigms in Gastric Cancer Staging: From Conventional Imaging to Advanced MRI and Artificial Intelligence
    Giovanni Balestrucci, Vittorio Patanè, Nicoletta Giordano, Anna Russo, Fabrizio Urraro, Valerio Nardone, Salvatore Cappabianca, Alfonso Reginelli · 2026 · Diagnostics
98. Data pipeline quality: development and validation of a quality assessment tool for data-driven algorithms and artificial intelligence in healthcare
    Eris van Twist, B. van Winden, Rogier de Jonge, Hendrik Rob Taal, Matthijs de Hoog, Alfred C. Schouten, David M. J. Tax, Jan Willem Kuiper · 2026 · BMJ Health & Care Informatics
99. Performance of Large Language Models for Radiology Report Impression Generation: A Systematic Review
    Curtise K. C. Ng, Zhonghua Sun, Ian K. H. Te · 2026 · Technologies
100. Beyond Algorithms: The Case for Standardized Reporting in AI Sleep Scoring
     Ahmed Salem BaHammam, Malak Abdullah Almarshad · 2026 · Nature and Science of Sleep