文章基本信息

标题：A MACHINE LEARNING APPROACH FOR IDENTIFYING DISEASE TREATMENT RELATIONS IN SHORT TEXTS
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作者：T.V.M. SAIRAM ; DR. G. RAMA KRISHNA
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：88
期号：3
出版社：Journal of Theoretical and Applied
摘要：The Machine learning (ML) region has proved its power in almost every industry and is currently a reliable technology in health care industry. Computerized study of the clinical industry includes suitable care choice guide, healthcare photo and DNA connections. ML is recognized as a tool employing computer systems integrating health care mechanisms resulting in more appropriate care and attention patients and further study or research on a disease. This paper provides powerful algorithms and techniques used in diagnosing illness using remedy associated phrases from brief published written text launched in health-care documents. The objective of this work is to show how Natural Language Processing (NLP) and Machine Learning strategies can be used for reflection of information and what class strategies are appropriate for determining & figuring out suitable care information in brief published written textual content. This paper additionally focuses on suitable care analysis therapy & prevention of contamination, infection harm in human. The system found out some assignment of clinical suitable care statistics, health-care control, and man or woman health data and so forth. The proposed method may be incorporated with any health-care management software to make better suitable care selection. The inpatient management application can instantly mine bio-medical data from virtual databases.
关键词：Health-Care; System Mastering; Natural Language Processing; Aid Vector Machine; Choice Aid System.