Enhancing Transparency and Trust in Healthcare Decision Support Systems through Explainability

Healthcare decision support systems help physicians in detecting, treating, and caring for sufferers. But the more complicated these computer systems expand, the more difficult it is to truly understand how they make rulings. To their processes to be trustworthy and reliable, they must be open and clear. By explaining the procedure for making choices, health care providers can analyze suggestions and make informed choices. Methods that aid in understanding findings involve highlighting key aspects, using basic concepts, and providing visual explanations. Further, it helps to ensure impartiality in treatment and decrease errors. Even with these techniques, it's still hard to strike the appropriate equilibrium between accuracy and clarity. In the healthcare industry, honest explanations enhance trust and responsible its use.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-03-17
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.39312
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Transparency and Trust in Healthcare Decision Support Systems through Explainability

S. Sathish, P Nanthini
International Journal For Multidisciplinary Research
Machine Learning in Healthcare
article

Enhancing Transparency and Trust in Healthcare Decision Support Systems through Explainability

S. Sathish, P Nanthini
article en

Abstract

Healthcare decision support systems help physicians in detecting, treating, and caring for sufferers. But the more complicated these computer systems expand, the more difficult it is to truly understand how they make rulings. To their processes to be trustworthy and reliable, they must be open and clear. By explaining the procedure for making choices, health care providers can analyze suggestions and make informed choices. Methods that aid in understanding findings involve highlighting key aspects, using basic concepts, and providing visual explanations. Further, it helps to ensure impartiality in treatment and decrease errors. Even with these techniques, it's still hard to strike the appropriate equilibrium between accuracy and clarity. In the healthcare industry, honest explanations enhance trust and responsible its use.

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 98%
Machine Learning in Healthcare
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