Transform heterogeneous health data into actionable knowledge through ML/AI(通过 ML/AI 将异构健康数据转化为可操作的知识)









主讲人:吴焕梅

报告人简介:

吴焕梅教授目前担任天普大学公共卫生学院卫生服务管理与政策系教授及系主任,并兼任学院全球事务助理院长。吴教授在数据科学、生物医学、健康信息和公共卫生等多个领域从事交叉学科研究,重点发现是数据整合、预测建模,机器学习,和精准治疗等方面。吴教授积极与学术界、各级卫生中心、研究机构、工业合作伙伴和当地社区紧密合作,致力于实现产学研用于一体的目标。她领导的多个课题获得包括美国国家科学基金会(NSF),美国国立卫生研究院(NIH),美国国际开发署(USAID),青少年糖尿病研究基金会(JDRF),罗伯特·伍德·约翰逊基金会(RWJF)等机构的资助。

报告摘要:

Within the dynamic healthcare landscape, the exponential growth of multi-modal, multi-level, and multi-sourced health data is evident. This presentation unravels the pivotal role and profound impact of Machine Learning (ML) and Artificial Intelligence (AI) in converting intricate and heterogeneous health data into actionable knowledge, such as strategies for personalized treatment plans, optimized hospital resource allocation, or reduced drug adverse events.  The talk highlights the synergistic capabilities of ML and AI by delving into systematic processes, including data integration, analysis, predictive modeling, and result interpretation. Attendees will gain insights into how these technologies empower evidence-based decision-making, driving transformative innovation in healthcare practices through real-world applications.

时间:2023-12-12 13:00:00

地点:松江校区1号学院楼140

组织单位:太阳集团tcy8722

主持人:陶然



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