Digital disease detection: Application of machine learning in community health informatics
© 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...
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th-cmuir.6653943832-413342017-09-28T04:20:41Z Digital disease detection: Application of machine learning in community health informatics Boonchieng E. Duangchaemkarn K. © 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. 2017-09-28T04:20:41Z 2017-09-28T04:20:41Z 2016-11-18 Conference Proceeding 2-s2.0-85006914043 10.1109/JCSSE.2016.7748841 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006914043&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/41334 |
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© 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. |
| format |
Conference Proceeding |
| author |
Boonchieng E. Duangchaemkarn K. |
| spellingShingle |
Boonchieng E. Duangchaemkarn K. Digital disease detection: Application of machine learning in community health informatics |
| author_facet |
Boonchieng E. Duangchaemkarn K. |
| author_sort |
Boonchieng E. |
| title |
Digital disease detection: Application of machine learning in community health informatics |
| title_short |
Digital disease detection: Application of machine learning in community health informatics |
| title_full |
Digital disease detection: Application of machine learning in community health informatics |
| title_fullStr |
Digital disease detection: Application of machine learning in community health informatics |
| title_full_unstemmed |
Digital disease detection: Application of machine learning in community health informatics |
| title_sort |
digital disease detection: application of machine learning in community health informatics |
| publishDate |
2017 |
| url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006914043&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/41334 |
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1681421982908809216 |