Exploring Healthcare Providers' Expectations and Perceptions of AI Machine Learning Decision Tree Models in Healthcare.

This paper investigates healthcare policymakers' and professionals' perceptions of Artificial Intelligence (AI) Machine Learning (ML) Decision Tree Models and their potential effects on clinical work processes. Semi-structured interviews with Dutch participants revealed nine key themes and 16 subthemes. Findings indicate that AI models are seen as supportive tools that can enhance care quality by automating repetitive tasks, freeing up time for patient-centred care. However, there is scepticism about significant time savings and increased patient turnover. Both groups emphasise the need for seamless integration with existing systems and comprehensive training to mitigate risks and improve adoption.