It is concluded that while generative AI holds transformative potential to reduce clerical burden and augment clinical reasoning, its successful deployment in emergency medicine requires rigorous attention to clinical safety, health equity, workflow integration, and human‑factors considerations.
It is concluded that while generative AI holds transformative potential to reduce clerical burden and augment clinical reasoning, its successful deployment in emergency medicine requires rigorous attention to clinical safety, health equity, workflow integration, and human‑factors considerations.
Klaudia Kwolek, Wiktoria Laskowska, M. Pilarek et al.· International Journal of Inn...· 0 citations
Generative AI demonstrably accelerates diagnostic workflows, augments scarce clinical datasets, personalizes communication, and supports discovery pipelines, and the paper concludes with a translational path and research priorities aimed at closing these gaps.
Wael Rahhal· Journal of Data Science and...· 0 citations
Although promising, LLM-based systems are not yet reliable enough for autonomous medical diagnosis, and multiple recommendations for future research are contained to ensure a high level of safety, transparency, and clinical applicability for LLMs and other AI/ML-related technologies and devices.
M. U. K. Gunawardhna, Pirunthavi Wijikumar, D. Weerasinghe· Sri Lankan Journal of Applie...· 1 citation
A scoping review with systematic evidence mapping across five electronic sources, screened 1,649 exportable records, and provisionally included 557 unique studies that met predefined criteria for goal-directed task execution, tool use, interaction with external resources, feedback-based refinement, or multi-agent colla...
Zheng Tong, Yang Liu, Wan-Shu Fan et al.· arXiv.org· 0 citations
This review examines key risk domains associated with the integration of GenAI into kidney care, including data-related challenges such as bias, limited representativeness, and data quality issues; technical limitations such as hallucinations and prompt-dependent variability; and cognitive risks, including automation b...
Elizabeth R. Viera Ramírez, L. F. de Arizón, Roser Torra et al.· Clinical Kidney Journal· 0 citations
A systematic review examines how personalization is operationalized in LLM-only and RAG-enhanced healthcare AI systems, finding that personalization remains inconsistently defined and weakly evaluated in healthcare AI, with most systems implementing retrieval-grounded adaptation rather than true patient-specific person...
Manal Althobaiti, Minhee Jun· Frontiers in Artificial Inte...· 0 citations
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