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Confidence miscalibration in medical AI can be mitigated, leading to both higher diagnostic accuracy and improved trust in clinical applications.
Ultrasound-CLIP leverages a new large-scale dataset and diagnostic taxonomy to achieve state-of-the-art performance in ultrasound image-text understanding, demonstrating the power of domain-specific pre-training.
