ArticleRadiology. Artificial intelligence2024
Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.
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In one paragraph
Article in Radiology. Artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–field-weighted citation impact
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of comparisons of AI and radiologists in the diagnosis of HCC in multiphase CT: implications for practice.Japanese journal of radiology · 2026Pooled it
- Evaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis.European radiology · 2025Pooled it
- Machine Learning-Based Prediction of 48-Hour Extubation Success in Mechanically Ventilated Children: A Single-Center Retrospective Cohort Study.Children (Basel, Switzerland) · 2026Article
- AI-Assisted Papillary Thyroid Carcinoma Localization on Cervical Non-contrast CT: A Multicenter Validation and Two-Reader Pilot Study of a Standalone Executable nnU-Net Software.Journal of imaging informatics in medicine · 2026Article
- Teaching AI for Radiology Applications: a Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM.Journal of imaging informatics in medicine · 2026Article
- Alignment of Policy, Practice, and Patient Safety for Trustworthy AI in Radiology.Radiology. Artificial intelligence · 2026Article
- Shifting from black box decisions to informed decision-making in using artificial intelligence to analyze prostate MRI.Abdominal radiology (New York) · 2026Review
- An Explainable Transformer-Based Framework for Lung Cancer Classification and Automated Radiology Report Generation from Multi-Slice CT Images.Biomedicines · 2026Article
- Foundation models for radiology: fundamentals, applications, opportunities, challenges, risks, and prospects.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Review
- Anticipating Moral and Economic Considerations, Opportunities, and Potential Frictions for AI in Medical Imaging: Multistakeholder Cocreation Study.Journal of medical Internet research · 2026Article
- State and Diffusion of National Institutes of Health Funding of AI in Radiology.Journal of imaging informatics in medicine · 2026Article
- From algorithms to operating room: can large language models master China's attending anesthesiology exam? A cross-sectional evaluation.International journal of surgery (London, England) · 2026Article
- From plug-and-play to institution-calibrated radiology AI: a practical framework for operationalizing local validation, monitoring and governance.Frontiers in radiology · 2026Article
- From scanner to scalpel: adapting IDEAL for accountable AI in radiology and image-guided neurosurgery.Frontiers in radiology · 2026Article
- Medical machine learning operations: a framework to facilitate clinical AI development and deployment in radiology.European radiology · 2025Review
- Teaching AI for Radiology Applications: A Multisociety‑Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM.Medical physics · 2025Article
- AI Revolution in Radiology, Radiation Oncology and Nuclear Medicine: Transforming and Innovating the Radiological Sciences.Journal of medical imaging and radiation oncology · 2025Review
- AI for Lesion Detection in Musculoskeletal Radiology.Journal of the Korean Society of Radiology · 2025Review
- AI-Powered Object Detection in Radiology: Current Models, Challenges, and Future Direction.Journal of imaging · 2025Review
- Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.Emergency radiology · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Marius George LinguraruFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0001-6175-8665
Spyridon BakasFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0001-8734-6482
Mariam AboianFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-4877-8271
Peter D ChangFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0001-7645-7865
Adam E FlandersFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-4679-0787
Jayashree Kalpathy-CramerFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0001-8906-9618
Felipe C KitamuraFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-9992-5630
Matthew P LungrenFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-8591-5861
John MonganFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0003-2765-7451
Luciano M PrevedelloFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-6768-6452
Ronald M SummersFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0001-8081-7376
Carol C WuFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0003-1005-0995
Maruf AdewoleFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-6562-2834
Charles E KahnFrom the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).ORCID 0000-0002-6654-7434
Funding
The Federated Tumor Segmentation (FeTS) platform: An intuitive tool facilitating secure multi-institutional collaborationU01CA242871 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BAKAS, SPYRIDON · 2019 to 2021
$1.1MComputer Aided Detection for Radiologic ImagesZIACL040004 · CLC · CLINICAL CENTER · PI SUMMERS, RONALD M. · 2009 to 2025
$0kNCI NIH HHS U01 CA242871
Abstract
The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of artificial intelligence (AI) in radiology. These conversations have collected viewpoints from multidisciplinary experts in radiology, medical imaging, and machine learning on the current clinical penetration of AI technology in radiology and how it is impacted by trust, reproducibility, explainability, and accountability. The collective points-both practical and philosophical-define the cultural changes for radiologists and AI scientists working together and describe the challenges ahead for AI technologies to meet broad approval. This article presents the perspectives of experts from MICCAI and RSNA on the clinical, cultural, computational, and regulatory considerations-coupled with recommended reading materials-essential to adopt AI technology successfully in radiology and, more generally, in clinical practice. The report emphasizes the importance of collaboration to improve clinical deployment, highlights the need to integrate clinical and medical imaging data, and introduces strategies to ensure smooth and incentivized integration.
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Artificial IntelligenceRadiologyHumansSocieties, MedicalAdults and PediatricsComputer Applications–General (Informatics)DiagnosisPrognosis
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