報(bào)告題目：Developing and deploying AI in National Health Services (NHS) in the UK: what are the realities?
時(shí)間：2024年8月26日（周一） 10:00
地點(diǎn)：中關(guān)村校區(qū)主樓429
報(bào)告人：李薇子教授
報(bào)告人簡(jiǎn)介：
Weizi (Vicky) Li is a Professor of Informatics and Digital Health, at Henley Business School, University of Reading. She is a Fellow of Charted Institute of IT (British Computer Society). She is an interdisciplinary researcher focusing on using informatics, data science, machine learning, and digital information systems to solve real-world healthcare challenges.
She has been Principal Investigators (PI) on large projects funded by the National Institute for Health and Care Research (NIHR), UK Research and Innovation (UKRI), NHS and industries working on data-driven decision support systems that use real-world data from multiple sources including Electronic Patient Records in acute, community hospital and primary care settings, to develop novel technologies (including AI-based methods) to support clinical and operational decision makings in patient pathways.
She is currently Director of Future Blood Testing for Inclusive Monitoring and Personalised Analytics NetworkPlus founded by UKRI Engineering and Physical Science Research Council (EPSRC); PI of UKRI EPSRC Technology mission fund in AI for Health project: Advancing machine learning to achieve real-world early detection and personalised disease outcome prediction of inflammatory arthritis; PI of NIHR Invention for Innovation Product Development Award: Machine learning-enabled decision support system to improve early detection and referral of rheumatic and musculoskeletal diseases.
Her work has been successfully implemented in NHS and has received the Research Engagement and Impact award in 2020 and 2022 and shortlisted for national Health Service Journal (HSJ) patient safety award.
報(bào)告內(nèi)容簡(jiǎn)介：
This seminar aims to delve into case studies of developing AI applications in National Health Services in the UK. While artificial intelligence has made substantial strides, the actual usability and widespread integration of AI within healthcare settings continue to present substantial challenges. This leads us to a critical question: How can we construct AI solutions leveraging healthcare data that are tailor-made to address the needs of frontline healthcare professionals effectively? Throughout this discussion, we will explore real-world AI case studies in UK healthcare and discuss challenges and opportunities for the development and implementation of AI within the real-world healthcare ecosystem.
