Ground Truth
Updated: 1 day ago
Ground Truth: Independent critical appraisal of healthcare AI research, emphasizing methodological flaws, misleading benchmarks, and patient.
Not all research is created equal. This is especially true in healthcare AI, where impressive claims about algorithm performance often rest on retrospective datasets, surrogate outcomes, or studies with significant methodological limitations. Ground Truth critically examines published AI research, looking beyond headlines and performance metrics to assess what the evidence supports.
This is evidence-based medicine (EBM) applied to AI. An algorithm that outperforms clinicians on a test dataset might be promising, but will it work in different clinical settings with different patient populations? More importantly, will it improve patient-important outcomes? Ground Truth encourages readers to question the methods, examine the results, and consider whether the conclusions are justified. It is an approach that fits naturally with HUMAI’s commitment to critical appraisal rather than accepting claims at face value.
Continuing the Conversation
Beyond HUMAI is intended to be an evolving collection of resources that complement our faculty's research, educational initiatives, and discussions about evidence-based medicine.
By sharing thoughtful perspectives from across the field, we hope to encourage informed debate, support critical appraisal, and contribute to a more responsible approach to AI in healthcare.
Our goal is not simply to follow the conversation about AI in medicine, but to help advance it.
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