Leveraging AI For Reliable And Automated Testing In Health Care Software Systems

The increasing reliance on healthcare software for clinical diagnostics, patient management, and hospital operations underscores the need for rigorous and efficient testing methodologies. Artificial Intelligence (AI) has emerged as a transformative force in the domain of software testing, particularly within high-stakes industries like healthcare. This paper investigates the application of AI techniques in automating software testing processes for healthcare systems. It emphasizes how AI improves test efficiency, ensures compliance, and reduces human error, while addressing the challenges of regulatory constraints and data privacy. Through analysis of existing tools and case implementations, the paper outlines current capabilities, risks, and future research directions.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-05-05
DOI
https://doi.org/10.36948/ijfmr.2025.v07i03.43640
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging AI For Reliable And Automated Testing In Health Care Software Systems

V Jamshina
International Journal For Multidisciplinary Research
Artificial Intelligence in Healthcare
article

Leveraging AI For Reliable And Automated Testing In Health Care Software Systems

V Jamshina
article en

Abstract

The increasing reliance on healthcare software for clinical diagnostics, patient management, and hospital operations underscores the need for rigorous and efficient testing methodologies. Artificial Intelligence (AI) has emerged as a transformative force in the domain of software testing, particularly within high-stakes industries like healthcare. This paper investigates the application of AI techniques in automating software testing processes for healthcare systems. It emphasizes how AI improves test efficiency, ensures compliance, and reduces human error, while addressing the challenges of regulatory constraints and data privacy. Through analysis of existing tools and case implementations, the paper outlines current capabilities, risks, and future research directions.

International Journal For Multidisciplinary ResearchVol. 7(3)
Openalex Percentile: Top 89%
Artificial Intelligence in Healthcare
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