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A Text Analytics-based E-Healthcare Decision Support Model Using Machine Learning Techniques
| Content Provider | Scilit |
|---|---|
| Author | Abdullah, A. Sheik Parkavi, R. Karthikeyan, P. Selvakumar, S. |
| Copyright Year | 2021 |
| Description | The domain of healthcare technology is facing many challenges in day-to-day scenarios with a major concern on the digitization process. Most conventions are being digitized for easy retrieval and analysis of healthcare data. Improving the issues and addressing the problems faced by the general population is mostly needed by medical experts and healthcare scientists. Healthcare information comes in various representations, such as images, text, categorical and continuous data, and unstructured parts. In considering the unstructured parts, the role of multimedia data plays a significant part in medical informatics. Meanwhile, data attribution plays a significant role with robustness and availability of data concerning biomedical applications. Handling structured data, such as categorical or continuous, reveals no issues or problems with analysis and interpretation. The most important part lies at the notion of handling the segments of unstructured data with tools and techniques that has been available with data analytics. Technology-based biomedical engineering created a vast difference and incorporation the following domains: Healthcare operations Healthcare infrastructure Data management/record maintenance Digital medicine Wellness/rehabilitation Pharmaceutical Healthcare research The objective of this chapter is to provide a text analytics-based e-healthcare decision support model using the incorporation of machine learning techniques and its applications. The mechanism of the text analytics-based model provides a complete way for data search, data extraction, interpretation, and evaluation. The algorithmic models and data distribution provides an active role in data generation and its constituent services. The algorithmic models corresponding to machine learning provide an efficient way of data handling and its services through text-based data retrieval with its available information retrieval models. Book Name: Smart Computational Intelligence in Biomedical and Health Informatics |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003109327-12&type=chapterpdf |
| Ending Page | 182 |
| Page Count | 14 |
| Starting Page | 169 |
| DOI | 10.1201/9781003109327-12 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-07-30 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Smart Computational Intelligence in Biomedical and Health Informatics Models Healthcare Decision Support Support Model Using Decision Support Model Based E Healthcare Machine Learning Techniques |
| Content Type | Text |
| Resource Type | Chapter |
