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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Taranath, NL Patil, Shantakumar B. Patil, Premajyothi Subbaraya, C.K. |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. Of CS & E, AIT, Chikmagalur, Karnataka, India (Taranath, NL; Subbaraya, C.K.) || Dept. Of CS & E, NCET, Bangalore, Karnataka, India (Patil, Shantakumar B; Patil, Premajyothi) |
| Abstract | This paper presents a novel framework for a decision support system that integrates knowledge-based and learning-based systems to provide a robust solution to the information challenge in the presence of partial information. It is suitable for many different healthcare settings and many different users, including physicians, nurses, and other medical staff. Because the framework is query-based, it can be adapted for use with many different end-user interfaces including desktop applications, web-based browser applications and mobile applications. In this work, we discuss a survey of proposed framework and a concrete implementation design to assist in clinical decisions regarding the prescription of sleeping aids. In addition we incorporate horizontal aggregations in SQL to prepare datasets for Data Mining analysis and Machine Learning based methodology for building an application that is capable of identifying and disseminating healthcare information. |
| Starting Page | 192 |
| Ending Page | 196 |
| File Size | 1466714 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479966295 |
| DOI | 10.1109/IC3I.2014.7019697 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-11-27 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems Learning-based systems Semantics Knowledge based systems Aggregations Medical services Data Mining Knowledge-based systems Data mining Medical diagnostic imaging SQL |
| Content Type | Text |
| Resource Type | Article |
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