Role Of Explainable AI In Diagnostics System

Author(s)	SHREYA GAUTAM WAGHMARE
Country	India
Abstract	Explainable Artificial Intelligence (XAI) is becoming increasingly critical in diagnostic systems, particularly in healthcare, where transparency and trust are paramount. XAI aims to make AI systems more interpretable by providing clear insights into how decisions are made, improving trustworthiness and regulatory compliance in medical diagnostics. This paper explores the role of XAI in diagnostic systems, outlining key methodologies, current applications, challenges, and potential future directions. Case studies are presented to demonstrate how explainable AI is integrated into diagnostic workflows, enhancing transparency and facilitating more informed decision-making by healthcare professionals.
Keywords	Explainable AI (XAI), Healthcare Diagnostics, Medical Imaging, Trust in AI, Interpretability , Clinical Decision Support Systems (CDSS) , Deep Learning , Transparency
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-01
Cite This	Role Of Explainable AI In Diagnostics System - SHREYA GAUTAM WAGHMARE - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.28060
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.28060
Short DOI	https://doi.org/g688vn

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