Challenges for implementing generative artificial intelligence (GenAI) into clinical healthcare.

Generative artificial intelligence (GenAI) is a form of deep learning AI based on inference that offers significant potential in healthcare. It has versatile capabilities: GenAI excels in complex human language communication, synthesising information from large and diverse datasets and performing br...

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Detalles Bibliográficos
Publicado en:Internal Medicine Journal Vol. 55; no. 7; pp. 1063 - 1070
Autores principales: Roberts, Lynden J., Jayasena, Rajiv, Khanna, Sankalp, Arnott, Leslie, Lane, Paul, Bain, Chris
Formato: review tables/charts Journal Article
Publicado: Wiley-Blackwell Jul2025
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Generative artificial intelligence (GenAI) is a form of deep learning AI based on inference that offers significant potential in healthcare. It has versatile capabilities: GenAI excels in complex human language communication, synthesising information from large and diverse datasets and performing broad, complex tasks reliably. Other important capabilities include scalability, 'always on' and cost effectiveness. Taken together, GenAI technology appears to possess considerable potential for healthcare. However, the implementation poses several challenges, including technological problems, regulatory considerations, workforce impact and building trust. Using evidence and expert opinion to explore these issues, the review aims to inform clinical experts about this rapidly evolving field.