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Fudan University
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Explicitly marking regions of interest in brain MRIs leads to a staggering 37.54% improvement in anomaly detection accuracy, transforming how diagnoses are made.
Fluent demonstrations may mislead robot learning, but a new representation method recovers critical motion insights, boosting performance significantly.
Agentic AI's fragility stems from relying on LLMs for system control, but Arbiter-K flips the script by using a deterministic kernel to govern the LLM, achieving up to 95% unsafe action interception.
An AI agent can now perform end-to-end echocardiography interpretation with 80% accuracy, rivaling human performance by integrating visual processing, measurement, and expert knowledge.
ColoDiff generates realistic colonoscopy videos with precise control over clinical attributes, offering a promising solution to data scarcity in intestinal disease diagnosis.
