A Review on Artificial Intelligence as a Solution to Burnout in Interventional Radiology.

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Title: A Review on Artificial Intelligence as a Solution to Burnout in Interventional Radiology.
Authors: Zhang H; Imperial College London, London, SW7 2AZ, UK. henry.zhang20@imperial.ac.uk., Torkpour A; Imperial College London, London, SW7 2AZ, UK., Zeidaabadi B; Imperial College London, London, SW7 2AZ, UK., Ashraf N; College of Medicine, Alfaisal University, Takhasusi Road, P.O. Box 50927, Riyadh, Saudi Arabia., Yazdabadi A; Eastern Health Clinical School, Monash University and Eastern Health, Melbourne, Australia., Iqbal SI; Massachusetts General Hospital, Boston Massachusetts, MA, 02114, USA., Asadi H; Neurointerventional Radiology Unit, Monash Health, Melbourne, Australia.; School of Medicine, Deakin University, Waurn Ponds, Geelong, Australia., Cazzato RL; Department of Interventional Radiology, University Hospital of Strasbourg, Strasbourg, France., Morgan R; St George's University Hospitals NHS Foundation Trust and St George's, Blackshaw Road, London, SW17 0QT, UK., Shaygi B; Imperial College London, London, SW7 2AZ, UK.; London North West University Healthcare NHS Trust, A404 Watford Rd, Harrow, HA1 3UJ, UK.
Source: Cardiovascular and interventional radiology [Cardiovasc Intervent Radiol] 2026 Apr 24. Date of Electronic Publication: 2026 Apr 24.
Publication Type: Journal Article; Review
Journal Info: Publisher: Springer Verlag Country of Publication: United States NLM ID: 8003538 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-086X (Electronic) Linking ISSN: 01741551 NLM ISO Abbreviation: Cardiovasc Intervent Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1432-086X
DOI:10.1007/s00270-026-04440-4