Assistant Tools for Medical Diagnostics through Rough Set-Based Data Analysis DOI Open Access

Kamesh Kumar

Indian Journal of Science and Technology, Journal Year: 2024, Volume and Issue: 17(31), P. 3174 - 3182

Published: Aug. 24, 2024

Objective: This study aims to identify and prioritize critical symptoms of pneumonia, determining their relative importance. Based on these findings, a decision rule base is developed enhance efficiency pneumonia diagnosis. Methods: A disease may concern with set symptoms, also same appear in different diseases. To make the diagnostic apparent, it advantageous assigning extra importance some symptoms. We applied reduction attributes indices rough theory characterize or core Thereafter, an algorithm has been proposed up assistant tools for medical Findings: The attribute, are calculated conditional namely respiratory rate (RR), cough level (CO), chest drawing (CI) temperature (T) concerned attribute (disease) pneumonia. findings reveal insights into identifying its degree likelihood Chest found list Also, Importance computed as 9/14 1/21, respectively. optimized assist process effectively. Novelty: research contributes presenting novel mathematical that identifies irrelevant disease. aids by redefining base. numerical computation provides practical visual tool assess potential outcomes technique. Applications: idea can experts better robust diagnostics when quantity increased linguistically expressed creates non-specificity type incompleteness. Keywords: Rough Set, Lower Upper Approximations, Indiscernibility Relation, Reduction Attribute, Medical Diagnosis

Language: Английский

A three-way efficacy evaluation approach with attribute reduction based on weighted temporal fuzzy rough sets DOI
Jin Ye, Bingzhen Sun, Xixuan Zhao

et al.

Information Sciences, Journal Year: 2025, Volume and Issue: 712, P. 122157 - 122157

Published: April 3, 2025

Language: Английский

Citations

0

Assistant Tools for Medical Diagnostics through Rough Set-Based Data Analysis DOI Open Access

Kamesh Kumar

Indian Journal of Science and Technology, Journal Year: 2024, Volume and Issue: 17(31), P. 3174 - 3182

Published: Aug. 24, 2024

Objective: This study aims to identify and prioritize critical symptoms of pneumonia, determining their relative importance. Based on these findings, a decision rule base is developed enhance efficiency pneumonia diagnosis. Methods: A disease may concern with set symptoms, also same appear in different diseases. To make the diagnostic apparent, it advantageous assigning extra importance some symptoms. We applied reduction attributes indices rough theory characterize or core Thereafter, an algorithm has been proposed up assistant tools for medical Findings: The attribute, are calculated conditional namely respiratory rate (RR), cough level (CO), chest drawing (CI) temperature (T) concerned attribute (disease) pneumonia. findings reveal insights into identifying its degree likelihood Chest found list Also, Importance computed as 9/14 1/21, respectively. optimized assist process effectively. Novelty: research contributes presenting novel mathematical that identifies irrelevant disease. aids by redefining base. numerical computation provides practical visual tool assess potential outcomes technique. Applications: idea can experts better robust diagnostics when quantity increased linguistically expressed creates non-specificity type incompleteness. Keywords: Rough Set, Lower Upper Approximations, Indiscernibility Relation, Reduction Attribute, Medical Diagnosis

Language: Английский

Citations

0