ReviewThe Indian journal of radiology & imaging2026
Artificial Intelligence in Neuroradiology: Transforming Diagnosis, Prognostication, and Workflow.
Review in The Indian journal of radiology & imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Abstract
Artificial intelligence (AI) is reshaping neuroimaging across the entirety of the clinical workflow, encompassing patient scheduling, scan quality assurance, image acquisition and reconstruction, automated lesion detection, pathological characterization, treatment planning, and outcome prognostication. This review synthesizes contemporary evidence through a workflow-centric framework, with particular emphasis on AI tools that have achieved real-world clinical implementation. Although reported technical performance across these domains is frequently compelling, critical deficiencies persist in external validation, human-AI benchmarking, model calibration, and standardized performance reporting, collectively impeding full clinical integration. Emerging evidence suggests that the role of the neuroradiologist is transitioning toward a collaborative human-AI paradigm, rather than one of displacement.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.