Maria Clarice R. Madrid, Ernesto G. Malaki, P. Ong, M. V. Solomo, Rizelle Anne L. Suntay, Heintjie N. Vicente
{"title":"医疗保健管理系统与销售分析使用自回归集成移动平均线和谷歌视觉","authors":"Maria Clarice R. Madrid, Ernesto G. Malaki, P. Ong, M. V. Solomo, Rizelle Anne L. Suntay, Heintjie N. Vicente","doi":"10.1109/HNICEM51456.2020.9400035","DOIUrl":null,"url":null,"abstract":"Digitalization of different industries led to new systems that provide accurate information that results in efficient and effective services. This information is vital for decision-making and on the larger scale, policymaking especially in the health sector. In the Philippines, some healthcare establishments have not adjusted to this digital change. This study aims to develop an enhanced model of healthcare management system that can perform digitization of data, predictive health analytics and sales trend analysis. The researchers identified these three features as the focus of the system because it improves data quality, accessibility, reliability, and autonomy. The system is based on prescriptive analytics - a type of analytics that uses machine learning to process historical and predictive data. The artificially intelligent management system caters to the needs of the healthcare sector in this digital age to improve its services to the people.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"5 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Healthcare Management System with Sales Analytics using Autoregressive Integrated Moving Average and Google Vision\",\"authors\":\"Maria Clarice R. Madrid, Ernesto G. Malaki, P. Ong, M. V. Solomo, Rizelle Anne L. Suntay, Heintjie N. Vicente\",\"doi\":\"10.1109/HNICEM51456.2020.9400035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digitalization of different industries led to new systems that provide accurate information that results in efficient and effective services. This information is vital for decision-making and on the larger scale, policymaking especially in the health sector. In the Philippines, some healthcare establishments have not adjusted to this digital change. This study aims to develop an enhanced model of healthcare management system that can perform digitization of data, predictive health analytics and sales trend analysis. The researchers identified these three features as the focus of the system because it improves data quality, accessibility, reliability, and autonomy. The system is based on prescriptive analytics - a type of analytics that uses machine learning to process historical and predictive data. The artificially intelligent management system caters to the needs of the healthcare sector in this digital age to improve its services to the people.\",\"PeriodicalId\":230810,\"journal\":{\"name\":\"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)\",\"volume\":\"5 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HNICEM51456.2020.9400035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM51456.2020.9400035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Healthcare Management System with Sales Analytics using Autoregressive Integrated Moving Average and Google Vision
Digitalization of different industries led to new systems that provide accurate information that results in efficient and effective services. This information is vital for decision-making and on the larger scale, policymaking especially in the health sector. In the Philippines, some healthcare establishments have not adjusted to this digital change. This study aims to develop an enhanced model of healthcare management system that can perform digitization of data, predictive health analytics and sales trend analysis. The researchers identified these three features as the focus of the system because it improves data quality, accessibility, reliability, and autonomy. The system is based on prescriptive analytics - a type of analytics that uses machine learning to process historical and predictive data. The artificially intelligent management system caters to the needs of the healthcare sector in this digital age to improve its services to the people.