Critical Care

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

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Subcategories: Sepsis
Showing 2584-2604 of 5,066 articles
MILD: Multi-Intent Learning and Disambiguation for Proactive Failure Prediction in Intent-based Networking

In multi-intent intent-based networks, a single fault can trigger co-drift where multiple intents ex...

Noradrenergic neuromodulation produces a NMDAR-dependent network state of respiratory rhythmogenesis in the preBotzinger Complex

Norepinephrine (NE) is an important mediator of sympathetic activity that influences breathing. At t...

Development and Validation of the Intensive Documentation Index for ICU Mortality Prediction: A Temporal Validation Study

Background: Nursing documentation patterns may reflect patient acuity and clinical deterioration, ye...

Deep Learning-Based Missing Value Imputation for Heart Failure Data from MIMIC-III: A Comparative Study of DAE, SAITS, and MICE+LightGBM

Background: Inadequate data in electronic health records can create problems for clinical decision s...

Enhancing Predictability of Multi-Tenant DNN Inference for Autonomous Vehicles' Perception

Autonomous vehicles (AVs) rely on sensors and deep neural networks (DNNs) to perceive their surround...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidn...

How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge

Large language models (LLMs) continue to struggle with knowledge-intensive questions that require up...

Kernel-Based Learning of Chest X-ray Images for Predicting ICU Escalation among COVID-19 Patients

Kernel methods have been extensively utilized in machine learning for classification and prediction ...

From Robotics to Sepsis Treatment: Offline RL via Geometric Pessimism

Offline Reinforcement Learning (RL) promises the recovery of optimal policies from static datasets, ...

Genomic Signatures and Prediction of Clinical Severity in Klebsiella pneumoniae infections in a Multicenter Cohort

Klebsiella pneumoniae is a major causative agent of hospital-acquired infections worldwide, contribu...

Self-Supervised Uncalibrated Multi-View Video Anonymization in the Operating Room

Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effecti...

Developing and externally validating machine learning models to forecast short-term risk of ventilator-associated pneumonia

Purpose: Ventilator-associated pneumonia (VAP) remains one of the most serious hospital-acquired inf...

AcceleRest: A Physiology-Aware Masked Autoencoder for Wrist Accelerometer-based Sleep Staging and Apnea Evaluation

Sleep is essential for physical and mental health, yet large-scale assessment of sleep stages and sl...

On Safer Reinforcement Learning Policies for Sedation and Analgesia in Intensive Care

Pain management in intensive care usually involves complex trade-offs between therapeutic goals and ...

De novo design of a safe and potent respiratory syncytial virus immuno-focusing antigen

Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infa...

Temporal Sepsis Modeling: a Fully Interpretable Relational Way

Sepsis remains one of the most complex and heterogeneous syndromes in intensive care, characterized ...

Why Large Language Models' Clinical Reasoning Fails: Insights from Explainable Deep Learning

BACKGROUND Medical large language models (LLMs) achieving high benchmark accuracy exhibit unexplaine...

Interpretable and backpropagation-free Green Learning for efficient multi-task echocardiographic segmentation and classification

Echocardiography is a cornerstone for managing heart failure (HF), with Left Ventricular Ejection Fr...

Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence

Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pedi...

LungCRCT: Causal Representation based Lung CT Processing for Lung Cancer Treatment

Due to silence in early stages, lung cancer has been one of the most leading causes of mortality in ...

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