您所在的位置: 头头体育直播吧» 头头体育直播吧» 讲座预告

【明理讲堂2020年第5期】台湾大学信息管理系魏志平教授:Natural Language Understanding of Biomedical Literature: Biomedical Relation Extraction Methods and Their App



头头体育直播吧腾讯会议号:296 459 659


The size of biomedical literature is massive and expands at a fast rate, due to the rapid growth in biomedical research and development. PubMed is an online portal (accessing primarily the MEDLINE database) that include more than 30 million of research articles (abstracts) on life sciences and biomedical topics by the end of January 2020. Biomedical literature provides healthcare practitioners (e.g., physicians, pharmacists) up-to-date biomedical research findings, which can be applied to improve professional practices and healthcare outcomes. Moreover, biomedical literature is core to new knowledge creation and discovery. Because the size of biomedical literature expands rapidly, manual review and inspection of biomedical research articles is very difficult and time-consuming. As a result, the development of some natural language understanding (NLU) techniques that can comprehend or extract important information from this huge collection of literature is essential and desirable.

One important type of information that can be extracted from these articles are biomedical relations discussed in each article. Examples of biomedical relations include drug-disease relations, chemical-protein relations, gene-disease relations, protein interactions, drug-drug interactions, etc. Formally, given a sentence (or a small segment of text) that contains two entities of interest, the task of  relation extraction is to predict whether the sentence describes some relation (out of a predefined set of relation types) between the two entities and, if so, to classify which relation class does the sentence point to. In this talk, I will present our proposed biomedical relation extraction methods that follow the deep-learning-based approach. In addition, in this talk, I will also discuss an important application of biomedical relation extraction, i.e., literature-based drug repurposing.



魏教授主要研究领域为大数据分析、文字探勘、社群媒体分析、生医信息、专利分析与探勘等,其研究成果发表于信息管理或信息科技相关领域之国际知名期刊中,例如 Journal of Management Information Systems (JMIS) 、 European Journal of Information Systems (EJIS) 、 Decision Sciences 、 Decision Support Systems (DSS) 、 Information & Management (I&M) 、 Journal of the Association for Information Science and Technology 、 IEEE Transactions in Engineering Management ,  IEEE Transactions on Systems, Man, and Cybernetics 、 IEEE Intelligent Systems 、 IEEE Transactions on Information Technology in Biomedicine 等。


w88优德官网登录|[最快路线]_网页版登录注册 必威体育注册网址|[最快路线] 银河网站地址|[最快路线] 威尼斯手机娱乐官网|[最快路线]_官方版APP下载 头头手机app下载|[最快路线]_官方版APP下载 巨奖联盟|[最快路线] 博亿堂手机网页登录|[最快路线]_官网APP下载 头头体育直播吧

TOP w88优德官网登录|[最快路线]_网页版登录注册 必威体育注册网址|[最快路线] 银河网站地址|[最快路线] 威尼斯手机娱乐官网|[最快路线]_官方版APP下载 头头手机app下载|[最快路线]_官方版APP下载 巨奖联盟|[最快路线] 博亿堂手机网页登录|[最快路线]_官网APP下载