Introducing CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement

The post outlines CARE‑X, a radiology vision‑language model designed to move beyond simple report generation. It combines flexible reasoning, calibrated predictions, and tool‑augmented measurement for chest X‑ray interpretation. The approach aims to make AI more clinically useful in radiology.

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