M. Z. Islam, Daizong Liu, Kewei Wang, Pan Zhou, Li Yu, D. Wu
{"title":"A Case Study of HealthCare Platform using Big Data Analytics and Machine Learning","authors":"M. Z. Islam, Daizong Liu, Kewei Wang, Pan Zhou, Li Yu, D. Wu","doi":"10.1145/3341069.3342980","DOIUrl":null,"url":null,"abstract":"The medical services in Bangladesh are shortage nowadays; people are suffering from getting the correct treatment from the hospital. With the low proportion of the doctors and the low per capita salary in Bangladesh, patients need to spend more money to get the appropriate treatments. Therefore, it is necessary to apply modern information technologies by which the scaffold between the patients and specialists can be reduced, and the patients can take proper treatment at a lower cost. Fortunately, we can solve this critical problem by utilizing interaction among electrical devices. With the big data collected from these devices, machine learning is a powerful tool for the data analytics because of its high accuracy, lower computational costs, and lower power consumption. This research is based on a case of study by the incorporation of the database, mobile application, web application and develops a novel platform through which the patients and the doctors can interact. In addition, the platform helps to store the patients' health data to make the final prediction using machine learning methods to get the proper healthcare treatment with the help of the machines and the doctors. The experiment result shows the high accuracy over 95% of the disease detection using machine learning methods, with the cost 90% lower than the local hospital in Bangladesh, which provides the strong support to implement of our platform in the remote area of the country.","PeriodicalId":411198,"journal":{"name":"Proceedings of the 2019 3rd High Performance Computing and Cluster Technologies Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 3rd High Performance Computing and Cluster Technologies Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3341069.3342980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The medical services in Bangladesh are shortage nowadays; people are suffering from getting the correct treatment from the hospital. With the low proportion of the doctors and the low per capita salary in Bangladesh, patients need to spend more money to get the appropriate treatments. Therefore, it is necessary to apply modern information technologies by which the scaffold between the patients and specialists can be reduced, and the patients can take proper treatment at a lower cost. Fortunately, we can solve this critical problem by utilizing interaction among electrical devices. With the big data collected from these devices, machine learning is a powerful tool for the data analytics because of its high accuracy, lower computational costs, and lower power consumption. This research is based on a case of study by the incorporation of the database, mobile application, web application and develops a novel platform through which the patients and the doctors can interact. In addition, the platform helps to store the patients' health data to make the final prediction using machine learning methods to get the proper healthcare treatment with the help of the machines and the doctors. The experiment result shows the high accuracy over 95% of the disease detection using machine learning methods, with the cost 90% lower than the local hospital in Bangladesh, which provides the strong support to implement of our platform in the remote area of the country.