Will AI Healthcare be reliable?

If the fundamental training data for medical AI systems is flawed, compromised, or based on junk science, then the AI models built upon it will inevitably inherit those imperfections. AI, at its core, learns from the data it's fed. If that data is inaccurate, biased, or reflects manipulated outcomes, the AI's diagnostic capabilities, treatment recommendations, and predictive analyses will be similarly flawed and potentially harmful. It's a classic case of "garbage in, garbage out"—the output quality of an AI system is directly constrained by the quality and integrity of its training data.

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