A pedagogical framework for integrating large language models into higher education in ways that strengthen, rather than replace, critical thinking.

Key findings of the WHO Europe report on AI readiness in health systems: adoption, governance gaps and what countries need to do next.

The GenAI divide: why most business generative AI pilots fail to deliver profits, based on the MIT NANDA 2025 report.

What influences nurses’ entrepreneurial ability, and strategies to develop it, based on a machine learning study.

Medical students’ digital health competences and beliefs about AI in evidence-based medicine: survey findings.

AI in healthcare: the promises, pitfalls and pathways forward for safe and effective adoption.

Neural mechanisms of hospital managers’ decision-making: what neuroscience reveals about administrative choices.

How artificial intelligence can support sustainable hospital management: applications, benefits and implementation challenges.

How AI is improving efficiency, accuracy and innovation in healthcare, with key applications and limitations.

AI in healthcare administration: opportunities for efficiency and decision-making, risks of bias and privacy, and what leaders need for adoption.

Navigating the doctor-patient-AI relationship: physician attitudes towards AI in primary care.

Healthcare professionals’ satisfaction with AI-based clinical decision support: what drives acceptance and use.

How generative AI capabilities drive green innovation in internationalising small and medium-sized enterprises.

How AI can support socially shared regulation of learning in online group work: focus groups with 30 students and seven TPACK-based design elements.

How accurate are AI chatbots in cardiovascular pharmacology education? An evaluation of answers to exam-style questions.

A scoping review of how artificial intelligence is integrated into nursing simulation and education.

Why some patients resist AI in healthcare: the psychological drivers of resistance and how to address them.

of AMEE Guide No. 178 on artificial intelligence in assessment in health professions education: uses, risks and good practice.

Why AI often fails to transform hospital practices: organisational, technical and human barriers.