Litcius/Paper detail

Challenges for implementing generative artificial intelligence (<scp>GenAI</scp>) into clinical healthcare

Lynden Roberts, Rajiv Jayasena, Sankalp Khanna, Leslie Arnott, Paul Lane, Chris Bain

2025Internal Medicine Journal10 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Generative grammarInferenceMedicineField (mathematics)Data scienceKnowledge managementScalabilityHealth careArtificial intelligenceApplications of artificial intelligenceComputer scienceDatabasePure mathematicsEconomicsEconomic growthMathematicsArtificial Intelligence in Healthcare and EducationHealthcare cost, quality, practicesClinical Reasoning and Diagnostic Skills
Challenges for implementing generative artificial intelligence (<scp>GenAI</scp>) into clinical healthcare | Litcius