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

Cited by (1,001)

Items 101–200 of 1,001

1. Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation
   Benoît Rizk, Hugues G. Brat, Pascal Zillé, Raphaël Guillin, Charlotte Pouchy, Chloé Adam, Roberto Ardon, Gaspard d’Assignies · 2021 · Physica Medica
2. CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies
   Salvatore Gitto, Renato Cuocolo, Domenico Albano, Francesco Morelli, Lorenzo Pescatori, Carmelo Messina, Massimo Imbriaco, Luca Maria Sconfienza · 2021 · Insights into Imaging
3. Radiomics and machine learning applications in rectal cancer: Current update and future perspectives
   Arnaldo Stanzione, Francesco Verde, Valeria Romeo, Francesca Boccadifuoco, Pier Paolo Mainenti, Simone Maurea · 2021 · World Journal of Gastroenterology
4. Critical Analysis of Artificial Intelligence in Endodontics: A Scoping Review
   Fahad Umer, Saqib Habib · 2021 · Journal of Endodontics
5. Artificial intelligence as a tool for diagnosis in digital pathology whole slide images: A systematic review
   João Pedro Mazuco Rodriguez, Rubens Rodriguez, Vitor Werneck Krauss Silva, Felipe Kitamura, Gustavo C.A. Corradi, Ana Carolina Bertoletti De Marchi, Rafael Rieder · 2022 · Journal of Pathology Informatics
6. How Radiomics Can Improve Breast Cancer Diagnosis and Treatment
   F. Pesapane, P. De Marco, A. Rapino, Eleonora Lombardo, Luca Nicosia, Priyan Tantrige, A. Rotili, A. Bozzini, S. Penco, V. Dominelli et al. · 2023 · Journal of Clinical Medicine
7. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA
   Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina E. Kottler, John Mongan, Lauren Oakden‐Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald et al. · 2024 · Radiology Artificial Intelligence
8. Deep learning for categorization of endodontic lesion based on radiographic periapical index scoring system
   Navas P. Moidu, Sidhartha Sharma, Amrita Chawla, Vijay Kumar, Ajay Logani · 2021 · Clinical Oral Investigations
9. Shallow and deep learning classifiers in medical image analysis
   Francesco Prinzi, Tiziana Currieri, Salvatore Gaglio, Salvatore Vitabile · 2024 · European Radiology Experimental
10. Delta radiomics: an updated systematic review
    Valerio Nardone, Alfonso Reginelli, Dino Rubini, Federico Gagliardi, Sara Del Tufo, Maria Paola Belfiore, Luca Boldrini, Isacco Desideri, Salvatore Cappabianca · 2024 · La radiologia medica
11. Detecting the presence of supernumerary teeth during the early mixed dentition stage using deep learning algorithms: A pilot study
    Yuichi Mine, Yuko Iwamoto, Shota Okazaki, Kentaro Nakamura, Saori Takeda, Tzu‐Yu Peng, Chieko Mitsuhata, Naoya Kakimoto, Katsuyuki Kozai, Takeshi MURAYAMA · 2021 · International Journal of Paediatric Dentistry
12. Artificial intelligence for body composition and sarcopenia evaluation on computed tomography: A systematic review and meta-analysis
    Sergei Bedrikovetski, Warren Seow, Hidde Maarten Kroon, Luke Traeger, James W. Moore, Tarik Sammour · 2022 · European Journal of Radiology
13. Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics
    Burak Koçak · 2022 · Diagnostic and Interventional Radiology
14. Influence of Magnetic Field Strength on Magnetic Resonance Imaging Radiomics Features in Brain Imaging, an In Vitro and In Vivo Study
    Samy Ammari, Stéphanie Pitre-Champagnat, Laurent Dercle, Émilie Chouzenoux, Salma Moalla, Sylvain Reuzé, Hugues Talbot, T. Mokoyoko, Joya Hadchiti, Sébastien Diffetocq et al. · 2021 · Frontiers in Oncology
15. Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence
    Joanna Marguerite Wardlaw, Grant Mair, Rüdiger von Kummer, Michelle Claire Williams, Wenwen Li, Amos Storkey, Emanuele Trucco, David S. Liebeskind, Andrew Farrall, Philip M. Bath et al. · 2022 · Stroke
16. COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients
    Isaac Shiri, Yazdan Salimi, Masoumeh Pakbin, Ghasem Hajianfar, Atlas Haddadi Avval, Amirhossein Sanaat, Shayan Mostafaei, Azadeh Akhavanallaf, Abdollah Saberi, Zahra Mansouri et al. · 2022 · Computers in Biology and Medicine
17. Applications of artificial intelligence in the analysis of dental panoramic radiographs: an overview of systematic reviews
    Natalia Turosz, Kamila Chęcińska, Maciej Adam Chęciński, Anita Brzozowska, Zuzanna Nowak, Maciej Sikora · 2023 · Dentomaxillofacial Radiology
18. Review of study reporting guidelines for clinical studies using artificial intelligence in healthcare
    Susan Cheng Shelmerdine, Owen John Arthurs, Alastair Keith Denniston, Neil James Sebire · 2021 · BMJ Health & Care Informatics
19. Artificial intelligence and urology: ethical considerations for urologists and patients
    Giovanni Enrico Cacciamani, Andrew W. Chen, Inderbir Singh Gill, Andrew J. Hung · 2023 · Nature Reviews Urology
20. How AI May Transform Musculoskeletal Imaging
    Ali Guermazi, Patrick Omoumi, Mickaël Tordjman, Jan Marie Fritz, Richard Kijowski, Nor-Eddine Regnard, John A. Carrino, Charles E. Kahn, Florian Knöll, Daniel Rueckert et al. · 2024 · Radiology
21. AI-enhanced breast imaging: Where are we and where are we heading?
    Almir Galvão Vieira Bitencourt, Isaac Daimiel Naranjo, Roberto Lo Gullo, Carolina Rossi Saccarelli, Katja Pinker · 2021 · European Journal of Radiology
22. The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation
    Yannick Suter, Urspeter Knecht, Waldo Valenzuela, Michelle Notter, Ekkehard Hewer, Philippe Schucht, Roland Wiest, Mauricio Reyes · 2022 · Scientific Data
23. Translating AI to Clinical Practice: Overcoming Data Shift with Explainability
    Choi, Youngwon, Yu, Wenxi, Nagarajan, Mahesh B., Teng, Pangyu, Goldin, Jonathan G., Raman, Steven S., Enzmann, Dieter R., Kim, Grace Hyun J., Brown, Matthew S. · 2023 · RadioGraphics
24. Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning
    Koçak, Burak, Cuocolo, Renato, Santos, Daniel Pinto dos, Stanzione, Arnaldo, Ugga, Lorenzo · 2023 · Balkan Medical Journal
25. AI Reporting Guidelines: How to Select the Best One for Your Research
    Klontzas, Michail E., Gatti, Anthony A., Tejani, Ali S., Kahn, Charles E. · 2023 · Radiology: Artificial Intelligence
26. 18F-FDG PET Maximum-Intensity Projections and Artificial Intelligence: A Win-Win Combination to Easily Measure Prognostic Biomarkers in DLBCL Patients
    Kibrom Berihu Girum, Louis Rebaud, Anne‐Ségolène Cottereau, Michel A. Meignan, Jérôme Clerc, Laëtitia Vercellino, Olivier Casasnovas, Franck Morschhauser, Catherine Thiéblemont, Irène Buvat · 2022 · Journal of Nuclear Medicine
27. Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges
    Stanzione, Arnaldo, Cuocolo, Renato, Ugga, Lorenzo, Verde, Francesco, Romeo, Valeria, Brunetti, Arturo, Maurea, Simone · 2022 · Cancers
28. Artificial intelligence for radiological paediatric fracture assessment: a systematic review
    Susan Cheng Shelmerdine, Richard White, Hantao Liu, Owen John Arthurs, Neil James Sebire · 2022 · Insights into Imaging
29. Automated classification of polyps using deep learning architectures and few-shot learning
    Adrian Krenzer, Stefan Heil, Daniel Fitting, Safa Matti, Wolfram G. Zoller, Alexander Hann, Frank Puppe · 2023 · BMC Medical Imaging
30. Impact of AI on radiology: a EuroAIM/EuSoMII 2024 survey among members of the European Society of Radiology
    Moreno Zanardo, Jacob J. Visser, Anna Colarieti, Renato Cuocolo, Michail E. Klontzas, Daniel Pinto dos Santos, Francesco Sardanelli, European Society of Radiology (ESR) · 2024 · Insights into Imaging
31. Deep learning for the classification of cervical maturation degree and pubertal growth spurts: A pilot study
    Hossein Mohammad‐Rahimi, Saeed Reza Motamedian, Mohadeseh Nadimi, Sahel Hassanzadeh-Samani, Mohammad A.S. Minabi, Erfan Mahmoudinia, Victor Y. Lee, Mohammad Hossein Rohban · 2022 · The Korean Journal of Orthodontics
32. A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks
    Adrian Krenzer, Michael Banck, Kevin Makowski, Amar Hekalo, Daniel Fitting, Joel Troya, Boban Sudarevic, Wolfram G. Zoller, Alexander Hann, Frank Puppe · 2023 · Journal of Imaging
33. Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review
    Sirwa Padash, Mohammad Reza Mohebbian, Scott J. Adams, Robert D. E. Henderson, Paul Babyn · 2022 · Pediatric Radiology
34. How Might AI and Chest Imaging Help Unravel COVID-19’s Mysteries?
    Shinjini Kundu, Hesham M. Elhalawani, Judy Wawira Gichoya, Charles E. Kahn · 2020 · Radiology Artificial Intelligence
35. Radiomics can differentiate high-grade glioma from brain metastasis: a systematic review and meta-analysis
    Yuanzhen Li, Yujie Liu, Yingying Liang, Ruili Wei, Wanli Zhang, Yao Wang, Shiwei Luo, Xinrui Pang, Ye Wang, Xinqing Jiang et al. · 2022 · European Radiology
36. Impact of Different Mammography Systems on Artificial Intelligence Performance in Breast Cancer Screening
    Clarisse Florence de Vries, Samantha J. Colosimo, Roger T. Staff, Jaroslaw Dymiter, Joseph E. Yearsley, Deirdre Dinneen, Moragh Boyle, David James Harrison, Lesley Ann Anderson, Gerald Lip et al. · 2023 · Radiology Artificial Intelligence
37. Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK
    Nikolaos Stogiannos, Rizwan Malik, Amrita Kumar, Anna Barnes, Michael Pogose, Hugh Harvey, Mark F. McEntee, Christina Malamateniou · 2023 · British Journal of Radiology
38. Machine intelligence in non-invasive endocrine cancer diagnostics
    Nicole M. Thomasian, Ihab R. Kamel, Harrison Xiao Bai · 2021 · Nature Reviews Endocrinology
39. Assessment of Radiology Artificial Intelligence Software: A Validation and Evaluation Framework
    William Tanguay, Philippe Acar, Benjamin Fine, Mohamed Abdolell, Bo Gong, Alexandre Cadrin-Chênevert, Carl Chartrand‐Lefebvre, Jean Chalaoui, Andrei Bogdan Gorgos, Anne Shu-Lei Chin et al. · 2022 · Canadian Association of Radiologists Journal
40. Medical Ethics of Large Language Models in Medicine
    Jasmine Chiat Ling Ong, Yin‐Hsi Chang, William Wasswa, Atul Janardhan Butte, Nigam Haresh Shah, Lita Sui Tjien Chew, Nan Liu, Finale Doshi‐Velez, Wei Lu, Julian Savulescu et al. · 2024 · NEJM AI
41. One Algorithm May Not Fit All: How Selection Bias Affects Machine Learning Performance
    Alice C. Yu, John Eng · 2020 · Radiographics
42. Deployed Deep Learning Kidney Segmentation for Polycystic Kidney Disease MRI
    Akshay Goel, George Shih, Sadjad Riyahi, Sunil Jeph, Hreedi Dev, Rejoice Hu, Dominick Romano, Kurt Teichman, Jon D. Blumenfeld, Irina Barash et al. · 2022 · Radiology Artificial Intelligence
43. Regulatory Aspects of the Use of Artificial Intelligence Medical Software
    Federica Zanca, Caterina Brusasco, Filippo Pesapane, Zuzanna Kwade, Ruth Beckers, Michele Avanzo · 2022 · Seminars in Radiation Oncology
44. Detecting pediatric wrist fractures using deep-learning-based object detection
    John R. Zech, Giuseppe Carotenuto, Zenas Igbinoba, Clement Vinh Tran, Elena Insley, Alyssa Baccarella, Tony T. Wong · 2023 · Pediatric Radiology
45. Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study
    Clemens P. Spielvogel, David Haberl, Katharina Mascherbauer, Jing Ning, Kilian Kluge, Tatjana Traub‐Weidinger, Rhodri Huw Davies, Iain Pierce, Kush P. Patel, THOMAS SELIM NAKUZ et al. · 2024 · The Lancet Digital Health
46. Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
    Qiang Wang, Changfeng Li, Jiaxing Zhang, Xiaojun Hu, Yingfang Fan, Kuansheng Ma, Ernesto Sparrelid, Torkel B. Brismar · 2021 · Cancers
47. Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram
    Jingyu Zhong, Chengxiu Zhang, Yangfan Hu, Jing Zhang, Yun Liu, Liping Si, Yue Xing, Defang Ding, Jia Geng, Qiong Jiao et al. · 2022 · European Radiology
48. A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation
    Imogen S. Stafford, Mark M. Gosink, Enrico Mossotto, Sarah Ennis, Manfred Hauben · 2022 · Inflammatory Bowel Diseases
49. How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts
    Burak Koçak, Ece Ateş Kuş, Özgür Kılıçkesmez · 2020 · European Radiology
50. Artificial intelligence–based image analysis in clinical testing: lessons from cervical cancer screening
    Didem Egemen, Rebecca B. Perkins, Li C. Cheung, Brian Befano, Ana Cecilia Rodríguez, Kanan T. Desai, Andréanne Lemay, Syed Rakin Ahmed, Sameer Antani, José Jerónimo et al. · 2023 · JNCI Journal of the National Cancer Institute
51. Deep learning models in classifying primary bone tumors and bone infections based on radiographs
    Hua Wang, Yu He, Lu Wan, Chenbei Li, Zhaoqi Li, Zhihong Li, Haodong Xu, Chao Tu · 2025 · npj Precision Oncology
52. The potential role for artificial intelligence in fracture risk prediction
    Hong, Namki, Whittier, Danielle E, Glüer, Claus-C, Leslie, William D · 2024 · The Lancet Diabetes & Endocrinology
53. Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms
    V. Bousson, Grégoire Attané, Nicolas Benoist, Laetitia Perronne, Abdourahmane Diallo, Lama Hadid‐Beurrier, Emmanuel Martin, L. Hamzi, Arnaud Depil-Duval, Eric Revue et al. · 2023 · Academic Radiology
54. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA
    Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina E. Kottler, John Mongan, Lauren Oakden‐Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald et al. · 2024 · Canadian Association of Radiologists Journal
55. Conventional and artificial intelligence-based imaging for biomarker discovery in chronic liver disease
    Jérémy Dana, Aïna Venkatasamy, Antonio Saviano, Joachim Lupberger, Yujin Hoshida, Valérie Vilgrain, Pierre Nahon, Caroline Reinhold, B. Gallix, Thomas F. Baumert · 2022 · Hepatology International
56. Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review
    Nikita Sushentsev, Nadia Moreira Da Silva, Michael Yeung, Tristan Barrett, Evis Sala, Michael T. Roberts, Leonardo Rundo · 2022 · Insights into Imaging
57. Comparing GPT-3.5 and GPT-4 Accuracy and Drift in Radiology Diagnosis Please Cases
    David K.B. Li, Kartik Gupta, Mousumi Bhaduri, Paul Sathiadoss, Sahir Bhatnagar, Jaron Chong · 2024 · Radiology
58. Classification of Dental Radiographs Using Deep Learning
    José Eduardo Cejudo Grano de Oro, Akhilanand Chaurasia, Ben Feldberg, Joachim Krois, Falk Schwendicke · 2021 · Journal of Clinical Medicine
59. MAIC–10 brief quality checklist for publications using artificial intelligence and medical images
    Leonor Cerdá-Alberich, Jimena Solana, Pedro Mallol, Gloría Ribas, Miguel García-Junco, Ángel Alberich‐Bayarri, Luis Martí‐Bonmatí · 2023 · Insights into Imaging
60. Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting
    Matthew Leming, Esther E. Bron, Rose Bruffaerts, Yangming Ou, Juan Eugenio Iglesias, Randy L. Gollub, Hyungsoon Im · 2023 · npj Digital Medicine
61. ARTIFICIAL INTELLIGENCE PLATFORMS IN DENTAL CARIES DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS
    Lyndon P Abbott, Ankita Saikia, Robert Prashanth Anthonappa · 2024 · Journal of Evidence Based Dental Practice
62. Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors
    Salvatore Gitto, Renato Cuocolo, Ilaria Emili, Laura Tofanelli, Vito Chianca, Domenico Albano, Carmelo Messina, Massimo Imbriaco, Luca Maria Sconfienza · 2021 · Journal of Imaging Informatics in Medicine
63. Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation
    Qiang Zhang, Anastasia Fotaki, Sona Ghadimi, Yu Wang, Mariya Doneva, Jens Wetzl, Jana G. Delfino, Declan P. O’Regan, Claudia Prieto, Frederick H. Epstein · 2024 · Journal of Cardiovascular Magnetic Resonance
64. Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms
    Hugh Pemberton, Jiaming Wu, Ivar O. Kommers, Domenique M. J. Müller, Yipeng Hu, Olivia Goodkin, Sjoerd B. Vos, Sotirios Bisdas, Pierre A. J. T. Robe, Hilko Ardon et al. · 2023 · Scientific Reports
65. Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study
    Aditya Rastogi, Gianluca Brugnara, Martha Foltyn‐Dumitru, Mustafa Ahmed Mahmutoglu, Chandrakanth Jayachandran Preetha, Erich Kobler, Irada Pflüger, Marianne Schell, Katerina Deike‐Hofmann, Tobias Keßler et al. · 2024 · The Lancet Oncology
66. Systematic review of machine learning-based radiomics approach for predicting microsatellite instability status in colorectal cancer
    Qiang Wang, Jianhua Xu, Anrong Wang, Yi Chen, Tian Wang, Danyu Chen, Jiaxing Zhang, Torkel B. Brismar · 2023 · La radiologia medica
67. Sociodemographic bias in clinical machine learning models: a scoping review of algorithmic bias instances and mechanisms
    Michael Colacci, Yu Qing Huang, Gemma Postill, Pavel Zhelnov, Orna Fennelly, Amol A. Verma, Sharon Elizabeth Straus, Andrea C. Tricco · 2024 · Journal of Clinical Epidemiology
68. Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making
    Jaryd R. Christie, Pencilla Lang, Lauren M. Zelko, David A. Palma, Mohamed Abdelrazek, Sarah A. Mattonen · 2020 · Canadian Association of Radiologists Journal
69. Artificial intelligence in computed tomography for quantifying lung changes in the era of CFTR modulators
    Gaël Dournes, Chase S. Hall, Matthew M. Willmering, Alan S. Brody, Julie Macey, S. Bui, Baudouin Denis de Senneville, Patrick Berger, François Laurent, Ilyès Benlala et al. · 2021 · European Respiratory Journal
70. Artificial Intelligence in Dentistry: A Concise Review of Reporting Checklists and Guidelines
    Zohaib Khurshid, Thanaphum Osathanon, Mohamedamin Abdullahi Shire, Falk Schwendicke, Lakshman Perera Samaranayake · 2025 · International Dental Journal
71. Towards reproducible radiomics research: introduction of a database for radiomics studies
    Akinci D’Antonoli, Tugba, Cuocolo, Renato, Baessler, Bettina, Pinto dos Santos, Daniel · 2023 · European Radiology
72. Artificial Intelligence for Automated Cancer Detection on Prostate MRI: Opportunities and Ongoing Challenges, From the AJR Special Series on AI Applications
    Baris Turkbey, Masoom A. Haider · 2021 · American Journal of Roentgenology
73. Lung Segmentation on High-Resolution Computerized Tomography Images Using Deep Learning: A Preliminary Step for Radiomics Studies
    Albert Comelli, Claudia Coronnello, Navdeep Dahiya, Viviana Benfante, Stefano Palmucci, Antonio Basile, Carlo Vancheri, Giorgio Ivan Russo, Anthony Joseph Yezzi, Alessandro Stefano · 2020 · Journal of Imaging
74. Machine learning prediction of hematoma expansion in acute intracerebral hemorrhage
    Satoru Tanioka, Tetsushi Yago, Katsuhiro Tanaka, Fujimaro Ishida, Tomoyuki Kishimoto, Kazuhiko Tsuda, Munenari Ikezawa, Tomohiro Araki, Yoichi Miura, Hidenori Suzuki · 2022 · Scientific Reports
75. Artificial intelligence model on chest imaging to diagnose COVID-19 and other pneumonias: A systematic review and meta-analysis
    Lu-Lu Jia, Jian-Xin Zhao, nini pan, Liuyan Shi, Lianping Zhao, Jinhui Tian, Gang Huang · 2022 · European Journal of Radiology Open
76. The reproducibility issues that haunt health-care AI
    Emily Sohn · 2023 · Nature
77. Combining clinical and imaging data for predicting functional outcomes after acute ischemic stroke: an automated machine learning approach
    Hongju Jo, Changi Kim, Dowan Gwon, Jae Ho Lee, Joonwon Lee, Kang Min Park, Seong-Ho Park · 2023 · Scientific Reports
78. Brain metastasis tumor segmentation and detection using deep learning algorithms: A systematic review and meta-analysis
    Tingwei Wang, Ming‐Sheng Hsu, Wei‐Kai Lee, Hung-Chuan Pan, Huai‐Che Yang, Cheng‐Chia Lee, Yu‐Te Wu · 2023 · Radiotherapy and Oncology
79. Reinventing Radiation Therapy with Machine Learning and Imaging Bio-markers (Radiomics): state-of-the-art, challenges and perspectives.
    L. Dercle, T. Henry, A. Carré, N. Paragios, É. Deutsch, C. Robert · 2020 · Methods
80. GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows
    Sarthak Pati, Siddhesh Pravin Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid, Bhakti Baheti, Megh Bhalerao, Orhun Güley, Sofia Mouchtaris, David Lang, Spyridon Thermos et al. · 2023 · Communications Engineering
81. Machine learning modeling practices to support the principles of AI and ethics in nutrition research
    Thomas, Diana M., Kleinberg, Samantha, Brown, Andrew W., Crow, Mason, Bastian, Nathaniel D., Reisweber, Nicholas, Lasater, Robert, Kendall, Thomas, Shafto, Patrick, Blaine, Raymond et al. · 2022 · Nutrition & Diabetes
82. Advancements in cardiac structures segmentation: a comprehensive systematic review of deep learning in CT imaging
    Turki Nasser Alnasser, Lojain Abdulaal, Ahmed Maiter, Michael J. Sharkey, Krit Dwivedi, Mahan Salehi, Pankaj Garg, Andrew J. Swift, Samer Alabed · 2024 · Frontiers in Cardiovascular Medicine
83. A fully automated deep learning approach for coronary artery segmentation and comprehensive characterization
    Guido Nannini, Simone Saitta, Andrea Baggiano, Riccardo Maragna, Saima Mushtaq, Gianluca Pontone, Alberto Cesare Luigi Redaelli · 2024 · APL Bioengineering
84. The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer
    William Tapper, Gustavo Carneiro, Christos Mikropoulos, Spencer A. Thomas, Philip Evans, Stergios Boussios · 2024 · Journal of Personalized Medicine
85. Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging
    Bettina Baeßler, Sandy Engelhardt, Amar Hekalo, Anja Hennemuth, Markus Hüllebrand, Ann P. Laube, Clemens Scherer, Malte Tölle, Tobias Wech · 2024 · Circulation Cardiovascular Imaging
86. Artificial intelligence for breast cancer detection and its health technology assessment: A scoping review
    Anisie Uwimana, Giorgio Gnecco, Massimo Riccaboni · 2024 · Computers in Biology and Medicine
87. Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study
    Chandrakanth Jayachandran Preetha, Hagen Meredig, Gianluca Brugnara, Mustafa Ahmed Mahmutoglu, Martha Foltyn‐Dumitru, et al, Michael Weller · 2021 · Zurich Open Repository and Archive (University of Zurich)
88. Validation of Artificial Intelligence Cardiac MRI Measurements: Relationship to Heart Catheterization and Mortality Prediction
    Samer Alabed, Faisal Alandejani, Krit Dwivedi, Kavita Karunasaagarar, Michael J. Sharkey, Pankaj Garg, Patrick J. H. de Koning, Attila Tóth, Yousef Shahin, Christopher Johns et al. · 2022 · Radiology
89. Artificial intelligence for the next generation of precision oncology
    Pedro J. Ballester, Javier Carmona · 2021 · npj Precision Oncology
90. Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes
    Anthony Ortiz, Anusua Trivedi, Jocelyn Desbiens, Marian S. Blazes, Caleb Robinson, Sunil R. Gupta, Rahul M. Dodhia, Pavan K. Bhatraju, Wayne Conrad Liles, Aaron Lee et al. · 2022 · Scientific Reports
91. Evaluation of an Artificial Intelligence web-based software to detect and classify dental structures and treatments in panoramic radiographs
    Mónica Bonfanti‐Gris, Ángel García-Cañas, Raúl Alonso-Calvo, María Paz Salido, Guillermo Pradies Ramiro · 2022 · Journal of Dentistry
92. Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke
    Martin Bretzner, Anna Katharina Bonkhoff, Markus D. Schirmer, Sung‐Min Hong, Adrian Vasile Dalca, Kathleen Donahue, Anne‐Katrin Giese, Mark R. Etherton, Pamela M. Rist, Marco Nardin et al. · 2022 · Neurology
93. Developing, purchasing, implementing and monitoring AI tools in radiology: Practical considerations. A multi‐society statement from the ACR, CAR, ESR, RANZCR & RSNA
    Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina E. Kottler, John Mongan, Lauren Oakden‐Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald et al. · 2024 · Journal of Medical Imaging and Radiation Oncology
94. Universal and extensible language-vision models for organ segmentation and tumor detection from abdominal computed tomography
    Jie Liu, Yixiao Zhang, Kang Wang, Mehmet Can Yavuz, Xiaoxi Chen, Yixuan Yuan, Haoliang Li, Yang Yang, Alan Yuille, Yucheng Tang et al. · 2024 · Medical Image Analysis
95. Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging
    Fereshteh Yousefirizi, Abhinav K. Jha, Julia Brosch-Lenz, Babak Saboury, Arman Rahmim · 2021 · PET Clinics
96. Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection
    Siddharth Agarwal, David A. Wood, Mariusz Tadeusz Grzeda, Chandhini Suresh, Munaib Din, James Howard Cole, Marc Modat A, Thomas Calvert Booth · 2023 · Clinical Neuroradiology
97. Automatic Segmentation with Deep Learning in Radiotherapy
    Lars Johannes Isaksson, Paul Eugene Summers, Federico Mastroleo, Giulia Marvaso, Giulia Corrao, Maria Giulia Vincini, Mattia Zaffaroni, Francesco Ceci, Giuseppe Petralia, Roberto Orecchia et al. · 2023 · Cancers
98. Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts? – A systematic review
    Olivier Rouvière, Tristan Jaouen, Pierre Baseilhac, Mohammed Lamine Benomar, Raphaël Escande, Sébastien Crouzet, Rémi Souchon · 2022 · Diagnostic and Interventional Imaging
99. AI in medical physics: guidelines for publication
    Issam El Naqa, John M. Boone, Stanley Benedict, Mitchell M. Goodsitt, Heang‐Ping Chan, Karen Drukker, Lubomir M. Hadjiiski, Dan Ruan, Berkman Sahiner · 2021 · Medical Physics
100. Deep Learning–based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts
     Daiju Ueda, Yutaka Katayama, Akira Yamamoto, Tsutomu Ichinose, Hironori Arima, Yusuke Watanabe, Shannon Leigh Walston, Hiroyuki Tatekawa, Hirotaka Takita, Takashi Honjo et al. · 2021 · Radiology