Artificial Intelligence (AI) is reshaping healthcare by enabling powerful advancements in areas such as medical diagnostics, drug development, patient interaction, and operational optimization. Despite these advancements, the integration of AI into clinical environments has been measured and deliberate. One of the primary challenges inhibiting broader adoption is the lack of explainability—the difficulty clinicians face in interpreting and trusting how AI-driven systems generate their outputs. In healthcare, where decisions can profoundly impact human lives, transparency extends beyond a technical concern and becomes an ethical necessity.
This paper examines the rising significance of Explainable AI (XAI) within healthcare and discusses how greater transparency can help close the trust gap between advanced technologies and clinical decision-making.
Read more here: Demystifying AI – The Rise of Explainability of AI in Healthcare
