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What are some of the key concerns around using AI for clinical decision-making?
In this installment of our Visionary Voices series, leading experts consider AI's limitations in healthcare and discuss how responsible AI implementation depends on understanding its limits while preserving the human element in healthcare decision-making.
Dr Rahul Goyal, Clinical Executive at Elsevier, continues his conversation with Dr Tamara Sunbul, Digital Health Transformation and Innovation Strategic Advisor, as they highlight three key concerns: AI models can inherit biases from training data, systems may produce diagnostic errors, and AI struggles with complex emotional and ethical scenarios. By empowering healthcare professionals with intelligent tools, we're creating pathways to smarter diagnostics, safer treatments, and truly personalized patient care.
What are some of the key concerns around using AI for clinical decision-making?
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