课程号：CS206005

课程名：智能医学与机器学习

英文课程名：Machine Learning in Smart Healthcare

开课单位：计算机科学与技术学院

授课教师：Shouyi Wang

王首懿

责任教师：宋胜利   徐悦甡

学分/学时：1学分/16学时

教师简介：王首懿博士现任美国德州大学工程学院终身教授，博士生导师，主要研究方向为大数据分析，人工智能，机器学习技术在智能医疗，智能信息管理系统，智能交通系统，智能制造，智能农业等方面的应用。王首懿博士是国际运筹学和管理学学会INFORMS会员，国际电气电子工程师学会IEEE会员，工业工程师学会IIE会员，担任国际运筹和管理学学会数据挖掘部理事会委员，美国国家自然科学基金（NSF）项目评审专家教授, 美华专业人士协会理事，国际脑信息学Brain Informatics委员会委员， 国际供应链技术杂志 (International Supply Chain Technology Journal) 副主编，国际运筹学杂志（Annals of Operations Research）特邀编辑, 国际脑信息学杂志(Brain Informatics) 副主编，2018年国际脑信息学年会论文集主编。国际学术类顶级出版社施普林格（Springer）特邀出版数据挖掘和机器学习论著一部。

Dr. Shouyi Wang is the Professor of College of Engineering at the University of Texas at Arlington, Arlington, TX. He is a Ph.D supervisor  and his research interests include data mining, machine learning, AI and deep learning technologies, healthcare informatics, medical decision-making systems, computational neuroscience, multivariate spatiotemporal time-series data mining. Prof. Wang is the member of several famous academic institutes, such as INFORMS (Institute for Operations Research and the Management Sciences), IEEE (Institute of Electrical and Electronics Engineers), IIE (Institute of Industrial and Systems Engineers) and Brain Informatics Committee. Prof. Wang is also the editor or associate editor of several prestigious international journals, including International Supply Chain Technology Journal, Annals of Operations Research, Brain Informatics and Proceedings of International Conference on Brain Informatics 2018. He is invited to publish a book on data mining and machine learning by the top academic press Springer.

课程简介：智能医学是指以现代医学与生物学理论为基础，融合脑认知、大数据、机器学习等人工智能及相关领域工程技术，研究人的生命和疾病现象的本质及其规律，探索人机协同的智能化诊疗方法和临床应用的新兴交叉领域。本课程将讲解最前沿的机器学习与人工智能基础理论知识，并介绍其在不同生物医学数据中的应用 （比如 医学影像学数据、基因组学数据、电子病历数据）。授课将采用理论加实验相结合的方式，并将机器学习理论知识融入到具体的医学数据分析案例中，希望有助于激发计算机专业学生对智能医疗健康领域的兴趣，提高教学效果。

Smart healthcare is formed with the combination of artificial intelligence and related technologies, such as brain cognition, big data and machine learning, and is based on modern medical and biological theory. Smart healthcare aims to study the fundaments and laws of human lives and diseases, and also aim to explore the emerging crossing areas of human-computer cooperation for intelligent diagnosis, treatment and clinic. This course will explain the edging theoretical basics of machine learning and artificial intelligence, and will also introduce the application in diverse biomedical data (i.e., medical images, genomics and medical records). The teaching will be carried out in both a theoretical way and experimental way, and will incorporate the theoretical knowledge into specific cases of medical data analysis. It is hoped to help stimulate the interest of students in the field of smart healthcare and improve teaching effect.

先修课程：程序设计语言、概率论、线性代数