Abstract:
Artificial Intelligence (AI) is reshaping healthcare, particularly in medical imaging, where its ability to deliver accurate diagnostics and tackle complex clinical problems offers groundbreaking promise. Yet translating raw data into real-world clinical applications remains an uphill battle. Medical imaging datasets are often intricate and varied, riddled with imbalances, limited annotations, and inconsistencies—flaws that can skew AI systems toward bias or inefficacy. This talk explores actionable solutions to these hurdles, emphasizing how clinical expertise, resource-smart learning approaches, and strategies to address crossing-demographics challenges can strengthen the dependability of AI-driven medical tools. I will also delve into the human side of AI integration, stressing the need for intuitive design, clinician trust, and cross-disciplinary partnerships to align cutting-edge innovation with the realities of healthcare practice. Ultimately, the success of AI in healthcare hinges on bridging two worlds: the technical brilliance of algorithms and the nuanced, ever-evolving demands of clinical environments. By embedding domain expertise directly into AI development, we can create systems that clinicians/public health experts want to use—tools that complement workflows rather than complicate them.

Bio:
Yanda Meng is an assistant professor (UK Lecturer) at the University of Exeter, Computer Science Department. His research is mainly at the interface of artificial intelligence and healthcare, specialised in the research and development of artificial intelligence, biomedical image processing and analysis techniques. He has published more than 40 papers in peer-reviewed journals and conferences such as IEEE Transactions on Medical Imaging, Medical Image Analysis, Diabetologia, Cardiovascular Diabetology, CVPR, ICCV, ECCV, AAAI, and MICCAI, etc. He has leadership roles as project PI delivering successful projects working effectively with different stakeholders (academics, clinicians, public, and industry). His collaboration with clinicians has made significant impacts on patient care. His research has been or is being supported by UKRI, UK Royal Society, Exeter Innovation, NHS Foundation Trust, and Welcome Trust.