Generative AI for Healthcare Students and Professionals

This course aims to provide healthcare students and professionals with a solid foundation of how generative AI is used in their sector adopting a balanced discourse of information. This will be achieved by using case studies that will analyse the current landscape of AI in different fields such as Higher Education, NHS, Public Health and Clinical Research. These case studies will be complemented by bioethics, confidentiality and humanistic perspectives of this technology. For a comprehensive, but yet concise, overview of the topic learners will also delve into the historical perspectives of AI. The course will conclude with final reflective thoughts on what the future might hold for healthcare in terms of utilising responsibly generative AI. As this is an introductory course on generative AI for healthcare, it will be targeted to students and qualified professionals who would like to learn more about this emerging technology in an easy-to-follow approach through the use of interactive case studies that will have real-world applications.

• Week 1 - Introduction to Generative AI in Professional Settings
• This week, we'll introduce the course, explore generative AI’s historical and emerging role in healthcare, and delve into AI and VR applications in medical imaging. We'll also discuss professional integrity, focusing on human oversight, and the impact of AI in academic and professional environments.
• Week 2 - Clinical Applications
• This week, we'll explore prompt engineering in AI for coding applications and develop an AI-generated application. We'll delve into generative AI's role in dental smile analysis, covering techniques like data augmentation and CNNs. We'll also learn about a multi-channel prediction model for pressure injuries in hospitalised patients. Lastly, we'll examine the ethical and humanistic aspects of AI in surgical training.
• Week 3 - National Health Service Applications
• This week, we’ll explore AI’s role in supporting COPD care pathways, considering both design and patient perspectives. We’ll delve into AI’s application in Scotland’s health and social care system, focusing on discrete event simulation and Bayesian methods. We’ll also learn about AI’s use in radiology for screening and diagnosis. Lastly, we’ll examine responsible AI use in research, emphasising accountability, authenticity, curiosity, and legacy, with a focus on ethical reflections and broader social implications.