應偉德國際1946bv官網的邀請，英國雷丁大學李微子教授于2024年8月26日上午10點在中關村校區主樓429會議室做了題為《Developing and deploying Al in National Health Services (NHS) in the UK: what are the realities?》的學術報告。報告會由顏志軍老師主持，學院眾多師生參加了本次報告會。
李教授的報告主要聚焦于英國國家衛生服務中的人工智能開發和應用。盡管人工智能已經取得了實質性進展，但人工智能在醫療保健環境中的實際可用性和廣泛集成仍然面臨著重大挑戰。因此，李教授針對如何構建人工智能解決方案、利用醫療保健數據有效地滿足一線醫療保健專業人員的需求開展了研究工作。
李教授通過兩個具體的人工智能研究案例向大家介紹了最新研究成果。首先，李教授以風濕病患者為例，指出由于英國患者就醫流程的復雜性和低效性，社區醫生難以準確判斷患者的風濕病類型并將其正確轉診到對應的醫院科室，導致許多風濕病患者的病情惡化，造成嚴重的社會健康問題。基于此，李教授基于社區醫院的就診病歷、過往就診信息和血液化驗記錄等多維度數據，采用深度學習方法對患者的風濕患病類型進行智能判斷，從而幫助社區醫生提高了風濕病患者的識別能力。同時，李教授從人工智能的可解釋性出發，研究了英國患者診療過程中常常出現的就診爽約問題，提出了基于深度學習的就診爽約預測算法，并建立了基于人工智能目標檢測的電話回訪機制，有效降低了英國社區醫院轉診后出現的居高不下的就診爽約率。
同時，李教授也分析了人工智能和醫療健康領域的未來研究方向，認為可以從大語言模型的角度出發，結合氣候、經濟、全球疾病負擔等多樣化的數據開展醫療健康領域的研究。
報告結束后，與會師生與李教授展開了積極的討論與交流。報告反響熱烈，得到了師生們的一致好評。
匯報人簡介：
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 onusing 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 operationaldecision makingsin patient pathways.
She is currently Director of Future Blood Testing for Inclusive Monitoring andPersonalised Analytics NetworkPlus founded by UKRI Engineering and PhysicalScience Research Council (EPSRC); PI of UKRI EPSRC Technology mission fund inAIfor Health proiect: Advancing machine learningto achieve real-worldearly detection and personalized disease outcome predictionofinflammatory arthritis; PI of NIHR Invention for Innovation Product Development Award: Machinelearning-enabled decision support system to improve early detection and referralofrheumatic and musculoskeletal diseases.
Her work has been successfully implemented in NHS and has received the Research Engagement and lmpact award in 2020 and 2022 and shortlisted for national Health Service Journal (HSJ) patient safety award.
