大数据时代妇产科计算生物学教学探索及思考

Exploration and Thinking on Teaching of Computational Biology in Obstetrics and Gynecology in Big Data Era

大数据驱动医学教育改革,在提供丰富教学资源的同时,也要求妇产科在内的医学教育增加大数据分析内容。计算生物学是有关生物大数据计算的前沿交叉学科,可为解析医学大数据提供高效方法。本文结合妇产科专业的数据特点及分析需求,融合计算生物学和妇产科学知识,采用PBL教学法,采用线上和线下相结合的方式进行理论教学,培养复合型医学人才。它不仅能提高学生的自主学习能力和数据处理能力,还能通过数据分析获得学生的行为指纹,有利于个性化教学和精准医学发展。

Big data drives the reform of medical education,which not only provides rich teaching resources,but also requires medical education,including obstetrics and gynecology,to increase the content of big data analysis.Computational biology is a cutting-edge interdisciplinary discipline related to biological big data computing,and can provide an efficient method for the analysis of medical big data.Combined with the data characteristics and analysis needs of obstetrics and gynecology major,this paper integrates the knowledge of computational biology and obstetrics and gynecology,adopts PBL teaching method and online-offline integration for theoretical teaching to cultivate composite medical talents.It can not only improve students'autonomic learning ability and data processing ability,but also obtain students'behavioral fingerprints through data analysis,which is conducive to personalized teaching and the development of precision medicine.