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Synthetic clinical benchmarks can be made significantly more realistic without sacrificing operational utility, challenging the assumption that utility alone guarantees quality. WHY_IT MATTERS: This work could fundamentally change how synthetic benchmarks are evaluated and optimized in healthcare AI, ensuring they are both useful and realistic.
