Clinical decision-making for multi-morbid patients requires synthesizing evidence from lengthy, fragmented records-a task that exposes the limitations of standard Retrieval-Augmented Generation (RAG) and long-context Large Language Models (LLMs), whi... read more
Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pediatric mortality worldwide. Echocardiography (echo) is central to diagnosing and triaging CHD, yet expert interpretation remains a scarce and maldistri... read more
Comprehending how forces are applied to an object during manipulation can help provide important insights into the quality of behavior in daily tasks. We have developed the Bead Maze Hand Function test to objectively measure the quality of hand funct... read more
Autism Spectrum Disorder standardized behavioral assessments provide quantitative measures of symptoms, yet their reliability and consistency have not been systematically evaluated. We present the first large-scale comparative analysis of four widely... read more
Conventional direction-of-arrival (DOA) estimation methods generally rely on the white Gaussian noise assumption, making them ineffective in hybrid noise scenarios. This paper proposes a deep neural network based on sparsely-gated mixture-of-experts ... read more
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