Evidence Map · e0003
Multimodal and Generative AI-Enabled Clinical Decision Support in Medicine: A PRISMA 2020-Informed Evidence Map and Narrative Synthesis
B.N. Sadykov, T.M. Saliev, K.K. Toguzbaeva, G.S. Bismildina, A. Tolegenkyzy, D.M. Ospanbekova. Multimodal and Generative AI-Enabled Clinical Decision Support in Medicine: A PRISMA 2020-Informed Evidence Map and Narrative Synthesis. Global Medical Reviews. 2026;1(1):e0003.
Abstract
Background
Multimodal and generative AI systems are increasingly proposed for clinical decision support, but the literature ranges from pragmatic trials to simulated consultations and benchmark-like evaluations.
Objective
To identify and synthesize empirical clinical and near-clinical evidence while keeping strict multimodal AI evidence separate from adjacent text-based generative AI clinical decision-support studies.
Methods
A structured, PRISMA 2020-informed evidence map and narrative synthesis covered clinician-facing studies published from 2018 to 9 July 2026.
Results
Seventeen empirical studies were included: 12 in the strict multimodal core and five in an expanded contextual set. Patient-important outcome evidence remained limited.
Conclusions
The evidence supports assistive, auditable, human-in-the-loop use for triage, documentation, decision preparation, second reading, and specialist workflow support. Autonomous deployment is not supported.
Keywords
Supplementary materials
No separate supplementary file has been deposited for this record. The Editorial Office must not present unverified or reconstructed files as original supplementary material.