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  • 标题:A Machine Learning Approach for Better Identification of Human Nature Based on the Current Health Care Data
  • 本地全文:下载
  • 作者:Gopinadh Sasubilli
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2019
  • 卷号:7
  • 期号:5
  • 页码:3129-3136
  • DOI:10.15680/IJIRCCE.2019. 0705088
  • 出版社:S&S Publications
  • 摘要:Machine Learning approaches are abundantly used over the globe for identification of different approaches related to real life scenario. There is a required scenario to be included in machine learning approach to identify the human nature based on his current health condition. A better health leads to a person to be active in all his activities and if at all he disturbs with anyone will distract him in all his activities until that issue resolves. Here what we mean is when a person is having a critical health issue and it will effect his/her current nature or mood which will effect that person in two ways. In this article we are presenting our research component which is to identify the current nature or mood of the person based on his health issues and what are the treatment he was given and how to predict the things related to him which he is going to be perform in future and what are the two things to be affected in his life because of the health issue and current nature he is having. This approach will use Neural Networks and other effective Machine Learning algorithms to design and effective prediction model which will help for the doctors, practitioners and also researchers to understand and perform better healthcare models and based on their requirement related to the patient. An effective deep learning approach will also help this research based on which we can map the relations between the health information systems and health information data. We need to correlate between data variables related to the scenario we are considering.
  • 关键词:Machine Learning; Deep Learning; Health Information System; Health Information Data; Prediction
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