Please use this identifier to cite or link to this item:
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55496
Title: | Digital disease detection: Application of machine learning in community health informatics |
Authors: | Ekkarat Boonchieng Khanita Duangchaemkarn |
Authors: | Ekkarat Boonchieng Khanita Duangchaemkarn |
Keywords: | Computer Science |
Issue Date: | 18-Nov-2016 |
Abstract: | © 2016 IEEE. Health informatics is a new research area which is interdisciplinary amongst information science, computer science and healthcare. The concept of health informatics is to develop a new way to manipulate healthcare data from various resources and devices by optimizing the method of data acquisition, data storage, data processing, and data visualization. Community health informatics can be described as the systematic application of information and computer science to obtain valuable data for solving health problems and providing it to health policy makers. The challenge of community health informatics is to maximize the efficiency and efficacy of big data analysis. This discussion paper aims to present the various applications of machine learning and software engineering approaches that implemented in digital disease detection. |
URI: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006914043&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55496 |
Appears in Collections: | CMUL: Journal Articles |
Files in This Item:
There are no files associated with this item.
Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.