Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Multimodal Deep Learning for Early Prediction of Patient Deterioration in the ICU: Integrating Time-Series EHR Data with Clinical Notes

Early identification of patients at risk for clinical deterioration in the intensive care unit (ICU)...

Fair Benchmarking of Emerging One-Step Generative Models Against Multistep Diffusion and Flow Models

State-of-the-art text-to-image models produce high-quality images, but inference remains expensive a...

ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation

While Multimodal Large Language Models (MLLMs) show promising performance in automated electrocardio...

SemiTooth: a Generalizable Semi-supervised Framework for Multi-Source Tooth Segmentation

With the rapid advancement of artificial intelligence, intelligent dentistry for clinical diagnosis ...

Ensuring Safety in Automated Mechanical Ventilation through Offline Reinforcement Learning and Digital Twin Verification

Mechanical ventilation (MV) is a life-saving intervention for patients with acute respiratory failur...

Automated extraction and optimization of protein purification protocols using multi-agent large language models

Recent advances in Large Language Models (LLMs) present new opportunities for automating critical bo...

Hospital AI and Robotics Adoption, Access Inequality, and County Mortality: A National Study Across 3,143 U.S. Counties

Hospital artificial intelligence (AI) and robotics are spreading unevenly across the United States, ...

AI-Powered Pipeline for Annotating Echocardiography Notes and Prognostic Variable Analysis in Critical Care

Abstract Background: Echocardiography (echo) notes contain valuable prognostic information for patie...

Association of Radiologic PPFE Change with Mortality in Lung Cancer Screening Cohorts

Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnor...

Multi-Kernel Gated Decoder Adapters for Robust Multi-Task Thyroid Ultrasound under Cross-Center Shift

Thyroid ultrasound (US) automation couples two competing requirements: global, geometry-driven reaso...

Predictors of COVID-19 hospital outcomes: a machine learning analysis of the National COVID Cohort Collaborative

Predicting hospital outcomes for patients with severe acute respiratory infections is critical for r...

TA-RNN-Medical-Hybrid: A Time-Aware and Interpretable Framework for Mortality Risk Prediction

Accurate and interpretable mortality risk prediction in intensive care units (ICUs) remains a critic...

LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Generative Real-World Super-Resolution

Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details f...

Unlocking ImageNet's Multi-Object Nature: Automated Large-Scale Multilabel Annotation

The original ImageNet benchmark enforces a single-label assumption, despite many images depicting mu...

Red-Teaming Medical AI: Systematic Adversarial Evaluation of LLM Safety Guardrails in Clinical Contexts

Background: Large language models (LLMs) are increasingly deployed in medical contexts as patient-fa...

KindSleep: Knowledge-Informed Diagnosis of Obstructive Sleep Apnea from Oximetry

Obstructive sleep apnea (OSA) is a sleep disorder that affects nearly one billion people globally an...

Bias in respiratory diagnoses by Large Language Models (LLMs) in Low Middle Income Countries (LMICs)

Introduction Clinicians and patients are likely to increasingly use Large Language Models (LLMs) for...

LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model

Accurate classification of autonomous vehicle (AV) driving behaviors is critical for safety validati...

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

As artificial intelligence systems move toward clinical deployment, ensuring reliable prediction beh...

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