MIMIC-IV-ED
PulseAugur coverage of MIMIC-IV-ED — every cluster mentioning MIMIC-IV-ED across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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New framework improves chest X-ray report generation with data compression
Researchers have developed ICGF-CXRMate, a novel framework designed to enhance the generation of clinical reports from chest X-ray images. This system addresses the challenge of integrating auxiliary patient data by com…
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New AI system PrivMeSA enhances medical LLM consultations while protecting patient privacy
Researchers have developed PrivMeSA, a novel multi-agent system designed to enhance medical consultations using large language models (LLMs) while preserving patient privacy. This system allows local agents to consult m…
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Open-source LLMs show promise for emergency department decision support
A new benchmark study evaluated eight open-source small language models (SLMs) for emergency department (ED) decision support, comparing them against commercial models like Claude Haiku 4.5 and Claude Sonnet 4.5. The re…
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New benchmark evaluates AI for dynamic emergency triage conversations
Researchers have introduced EHR2Dial-Triage, a new framework and benchmark designed to evaluate conversational AI agents in emergency department triage. This system is grounded in electronic health records (EHRs) and si…
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New ML model improves emergency triage with incomplete clinical data
Researchers have developed CRS-Triage, a novel machine learning approach designed to improve emergency room triage accuracy, particularly when electronic health record data is incomplete or unreliable. This system estim…
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Machine learning models evaluated for imbalanced clinical data
A new study published on arXiv explores the effectiveness of various machine learning models for predicting critical care outcomes using imbalanced clinical data. Researchers evaluated six model families, including tree…
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LLMs show significant gender bias in medical triage, study finds
A new audit called EQUITRIAGE evaluated five large language models for gender bias in emergency department triage, finding that all models exhibited bias above a 5% threshold. DeepSeek-V3.1 and Gemini-3-Flash showed sig…