Shahidul Islam Khan, Arman Shaharia, Nazmul Islam, Md. Monirul Islam, A. S. M. Latiful Hoque
{"title":"利用机器学习技术改善社区诊所的医疗服务","authors":"Shahidul Islam Khan, Arman Shaharia, Nazmul Islam, Md. Monirul Islam, A. S. M. Latiful Hoque","doi":"10.1109/ICISET.2018.8745568","DOIUrl":null,"url":null,"abstract":"Healthcare in Bangladesh has witnessed rapid growth in the recent past. A vast amount of data is generated in health sector of Bangladesh every day. Machine learning (ML) has a wide range of applications in healthcare. This paper highlights a brief overview of the applications of ML in healthcare. In this paper, we used ML techniques to predict different outpatient amounts of community clinics. We collected a dataset of 14889 patients within a time span of 508 days, from Community Clinics in Sandwip. In our research, we predicted the day of the week when maximum female and infant patients come into the community clinic for treatment. So the clinic authority may arrange support staffs accordingly. We used multiple linear regression and support vector regression for this purpose. Experimental results show that we could predict the amount of different types of outpatient visit with minimum error.","PeriodicalId":6608,"journal":{"name":"2018 International Conference on Innovations in Science, Engineering and Technology (ICISET)","volume":"118 1","pages":"437-441"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improving Healthcare Services of Community Clinics using Machine Learning Techniques\",\"authors\":\"Shahidul Islam Khan, Arman Shaharia, Nazmul Islam, Md. Monirul Islam, A. S. M. Latiful Hoque\",\"doi\":\"10.1109/ICISET.2018.8745568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare in Bangladesh has witnessed rapid growth in the recent past. A vast amount of data is generated in health sector of Bangladesh every day. Machine learning (ML) has a wide range of applications in healthcare. This paper highlights a brief overview of the applications of ML in healthcare. In this paper, we used ML techniques to predict different outpatient amounts of community clinics. We collected a dataset of 14889 patients within a time span of 508 days, from Community Clinics in Sandwip. In our research, we predicted the day of the week when maximum female and infant patients come into the community clinic for treatment. So the clinic authority may arrange support staffs accordingly. We used multiple linear regression and support vector regression for this purpose. Experimental results show that we could predict the amount of different types of outpatient visit with minimum error.\",\"PeriodicalId\":6608,\"journal\":{\"name\":\"2018 International Conference on Innovations in Science, Engineering and Technology (ICISET)\",\"volume\":\"118 1\",\"pages\":\"437-441\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Innovations in Science, Engineering and Technology (ICISET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISET.2018.8745568\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Innovations in Science, Engineering and Technology (ICISET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISET.2018.8745568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Healthcare Services of Community Clinics using Machine Learning Techniques
Healthcare in Bangladesh has witnessed rapid growth in the recent past. A vast amount of data is generated in health sector of Bangladesh every day. Machine learning (ML) has a wide range of applications in healthcare. This paper highlights a brief overview of the applications of ML in healthcare. In this paper, we used ML techniques to predict different outpatient amounts of community clinics. We collected a dataset of 14889 patients within a time span of 508 days, from Community Clinics in Sandwip. In our research, we predicted the day of the week when maximum female and infant patients come into the community clinic for treatment. So the clinic authority may arrange support staffs accordingly. We used multiple linear regression and support vector regression for this purpose. Experimental results show that we could predict the amount of different types of outpatient visit with minimum error.