| Type of Material: | Thesis |
| Title: | Enhancement of features and characteristics of rough set and their implementation for developing an efficient medical diagnosis system |
| Researcher: | Sahu, Indrani Kumari |
| Guide: | Das, Susanta Kumar |
| Department: | Department of Computer Science |
| Publisher: | Berhampur University, Berhampur |
| Place: | Berhampur |
| Year: | 2022 |
| Language: | English |
| Subject: | Computer Science | Computer Science Interdisciplinary Applications | Engineering and Technology | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Computer Science, Berhampur University, Berhampur, Berhampur; 2022 |
| Fulltext: | Shodhganga |
| 003 | IN-AhILN | |
| 005 | 2026-10-16 17:04:03 | |
| 008 | __ | 261016t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_464373 |
| 040 | __ | |dIN-AhILN|aBRMP_760007 |
| 041 | __ | |aeng |
| 100 | __ | |eResearcher|aSahu, Indrani Kumari |
| 110 | __ | |aDepartment of Computer Science|0U-0350|dBerhampur|bBerhampur University, Berhampur|ein |
| 245 | __ | |aEnhancement of features and characteristics of rough set and their implementation for developing an efficient medical diagnosis system |
| 260 | __ | |aBerhampur|c2022|bBerhampur University, Berhampur |
| 300 | __ | |a204p.|dDVD |
| 502 | __ | |cDepartment of Computer Science, Berhampur University, Berhampur, Berhampur|d2022|bPhD |
| 518 | __ | |oDate of Award|d2022 |
| 518 | __ | |d2015|oDate of Registration |
| 518 | __ | |oDate of Completion|d2022 |
| 520 | __ | |aIn recent decades, there have been phenomenal improvements in the patient s health care system including disease prevention, diagnosis, treatments and prognosis management. Recent COVID-19 outbreak and growing health risk are stemming towards a new dimension of health care, prevailing the physical and mental disabilities in people. With the motto Diagnosis Is Better Than Disease , the system aims in protecting patient s health and associated cost. Patient history,diagnostic information are crucial in clinical decision making and with technological support of bio sensors, IoT devices and mobile clinical equipments, the system collects large data and often raise issues of data uncertainty, ambiguity and dimensionality. Rough set theory (RST) manages the modeling of categories and decision-making problems that include vague, inaccurate, imprecise or incomplete information. With these sensitive issues in mind, the culmination of this thesis is focused on the use of RST and its feature advancements and to develo |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aComputer Science Interdisciplinary Applications |
| 653 | __ | |aEngineering and Technology |
| 700 | __ | |aDas, Susanta Kumar|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/409168|yShodhganga |
| 905 | __ | |afromsg |
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