Cros: risk-constrained stopping for clinical diagnosis agents
A stopping layer that tries to decide when a sequential diagnosis agent should diagnose or defer — with finite-sample style tests, and an honest ‘exploratory, not confirmatory’ framing.
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A stopping layer that tries to decide when a sequential diagnosis agent should diagnose or defer — with finite-sample style tests, and an honest ‘exploratory, not confirmatory’ framing.
A medical imaging methods note: small pulmonary nodules show a Gaussian radial intensity prior; GRIPNet designs every module around that physics and reports strong mAP@0.5 on three public CT benchmarks.
Self-hosted Llama extracts structured T-stage from radiology reports with source-text links — 90% accuracy vs a four-expert reference on 130 reports.
A living eval suite of 43 biomedical HDLSS datasets across 28 feature×sample operating points — tabular foundation models lead at the reference cell, but logistic regression stays uncomfortably close.