日 期 : 115年06月03日(三)
時 間 ：13:30 ~ 14:50
地 點 ：語文館LAN007
主講人 ：蘇家玉 教授(國立陽明交通大學 生物醫學資訊研究所)
講 題 ：How AI is Changing the Future of Healthcare
Artificial intelligence (AI) and machine learning (ML) are increasingly applied to healthcare, where large volumes of biological and clinical data are generated daily. This talk introduces how AI techniques can be used to analyze health-related data and support better decision-making in medicine and public health. The presentation will begin with an overview of health data, including molecular data, medical images, clinical records, and population health datasets. It will then demonstrate how machine learning models can be trained to identify patterns in these complex datasets to assist tasks such as disease prediction, medical diagnosis, and health risk monitoring. A key focus of the talk is Explainable AI (XAI), which aims to make machine learning models more transparent and interpretable. In healthcare applications, it is important not only to build accurate models but also to understand why a model makes certain predictions. Explainable AI techniques can help clinicians and researchers interpret model outputs and increase trust in AI-assisted decision support systems. Several real-world case studies will be introduced, including applications in bioinformatics, reproductive health, ophthalmology, and infectious disease forecasting. These examples illustrate how AI models can transform raw biomedical data into meaningful insights that support both clinical practice and public health decision-making. Through these examples, the talk highlights how students with backgrounds in computer science and data science can contribute to solving important healthcare challenges by developing robust, interpretable, and impactful AI solutions.