Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine by Mehul

Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine by Mehul

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Artificial Intelligence (AI) has revolutionized various industries, including healthcare. One of the key aspects of AI in healthcare is explainable AI, which aims to make the decision-making process of AI systems transparent and understandable to humans. In his book “Unboxing Machine Learning for Biomedicine,” Mehul explores the concept of explainable AI in healthcare and its implications for the field of biomedicine.

Explainable AI in healthcare is essential for building trust in AI systems, ensuring accountability, and enabling healthcare professionals to understand the reasoning behind AI-driven decisions. Mehul delves into the various techniques used in explainable AI, such as interpretable machine learning models, post-hoc explanations, and model transparency measures.

By demystifying the black box of AI algorithms, explainable AI in healthcare can help improve patient outcomes, enable personalized medicine, and enhance clinical decision-making. Mehul’s book provides valuable insights into how explainable AI can be applied in the context of biomedicine, offering a roadmap for healthcare practitioners, researchers, and policymakers to harness the power of AI in a responsible and ethical manner.

“Unboxing Machine Learning for Biomedicine” is a must-read for anyone interested in the intersection of AI and healthcare, shedding light on the potential of explainable AI to transform the future of medicine.
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