Forbes March 17, 2025
Artificial intelligence (AI) is rapidly transforming medicine, promising to revolutionize diagnostics, treatment planning and operational efficiency. But there’s a critical—and often overlooked—flaw in many AI-driven healthcare models: They are only as good as the data they are trained on.
For AI to truly improve and standardize healthcare delivery, we must confront a fundamental issue—the limited and often siloed nature of clinical data. If institutions and health systems continue to train AI models solely within their own populations and geographic regions, they risk developing highly performant yet ultimately narrow-scope solutions. These models may excel in their specific environments but falter when applied broadly, leading to skepticism, reduced adoption and even potential harm due to unrecognized biases.
To create AI models that...
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