Ahthasham Sajid, M. Awais, Mirza Amir Mehmood, S. Batool, Amir Shahzad, A. Zafar
{"title":"基于“自由文本分析”的医疗保健行业患者服务质量反馈平台","authors":"Ahthasham Sajid, M. Awais, Mirza Amir Mehmood, S. Batool, Amir Shahzad, A. Zafar","doi":"10.24003/emitter.v8i2.502","DOIUrl":null,"url":null,"abstract":"Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patient's experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Results achieved have shown 88 % accuracy in predicting whether or not a patient will recommend the service. Based on which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.","PeriodicalId":14142,"journal":{"name":"International journal of engineering and technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry\",\"authors\":\"Ahthasham Sajid, M. Awais, Mirza Amir Mehmood, S. Batool, Amir Shahzad, A. Zafar\",\"doi\":\"10.24003/emitter.v8i2.502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patient's experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Results achieved have shown 88 % accuracy in predicting whether or not a patient will recommend the service. Based on which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.\",\"PeriodicalId\":14142,\"journal\":{\"name\":\"International journal of engineering and technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of engineering and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24003/emitter.v8i2.502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of engineering and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24003/emitter.v8i2.502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry
Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patient's experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Results achieved have shown 88 % accuracy in predicting whether or not a patient will recommend the service. Based on which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.