Critical Care

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

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Subcategories: Sepsis
Showing 2395-2415 of 5,066 articles
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback

Embodied coding agents construct robot policies from natural-language instructions by generating exe...

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Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents

Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (...

SimAuthor: Harnessing Foundation Models for Persistent Scientific Simulator Authoring

Foundation models can generate scientific code, but authoring a scientific simulator (an executable ...

LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models

Time-series data are often sampled irregularly at high frequencies and exhibit long-range dependenci...

Multi-task learning for the automatic grading of enlarged perivascular space burden using MRI

Enlarged perivascular spaces (PVS) visible in brain magnetic resonance imaging (MRI) are increasingl...

Genome-Wide Association Study of Sepsis Susceptibility in ICU Patients Identifies Arab Founder Loss-of-Function Variant in UBE2L3

Sepsis causes approximately 11 million deaths globally each year. Whole-genome sequencing (WGS) of f...

Where Tabular Foundation Models Falter on Genetic Data: Datasets That Expose and Provide a Path to Address the Gap

Tabular foundation models are used as off-the-shelf predictors for heterogeneous tabular tasks, but ...

ResonAct: Streaming Metrics for Runtime Diagnosis and Self-Healing in Multi-Agent Systems

Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple ...

MTLiquid: Enabling Efficient Multi-Task Learning using Liquid Neural Networks for Lightweight Healthcare Monitoring Systems

Continuous-time sensing and monitoring with timely and accurate decision-making are critical for man...

Feedback-Robust AI for Patient Knowledge Graphs

Patient knowledge graphs from bedside monitoring should type their relations and state whether the d...

M3-Score: Fidelity, Memorization and Coverage as Separate Axes for Evaluating Generative Radiology Image Models

Quantitative evaluation of generative models for radiology remains challenging. Clinically relevant ...

BreathGRU: A Novel Semi-Supervised Bidirectional Gated Recurrent Unit Framework for Speech and Breath Segmentation for Respiratory Audio

Speech-breath segmentation is a fundamental preprocessing step in respiratory audio analysis, enabli...

Hi-OPD: Hierarchy-Aware Open-Prompt Detection for Remote Sensing Images

Hi-OPD addresses a failure mode left uncontrolled by flat open-prompt training: descendant retrieval...

GLR-MM: Graph-Based Global-Local Reconstruction for Robust Multimodal Chest X-ray and EHR Representation Learning under Missing Modalities

Clinical multimodal models must often predict before all chest X-ray (CXR) and electronic health rec...

Intervention Granularity Matters: Coherent Treatment Bundles in Counterfactual Simulation with Clinical World Models

Counterfactual simulation with a clinical world model means fixing a patient's history, changing the...

Threat imminence and estimates of agency dictate proactive and reactive defensive behaviors in active place avoidance

Defensive survival behaviors are shaped by both danger attributes and internal physiological states....

Representing Clinical Conditions on Vital Signs from Healthy Individuals using Latent Modeling

Machine learning can be crucial to help scale complex signal processing applications in scenarios su...

DualStream-MTCA: A Hybrid Deep Learning Model for the Simultaneous Early Detection of Sepsis and Heart Failure in Adult Intensive Care

Sepsis and heart failure share early-warning physiology but require divergent treatments, complicati...

Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection

The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswin...

When does a spectral prior help graph learning? Connectivity-loss estimation under road-network disruptions

Rapid evaluation of many simultaneous road-link disruptions requires a practical compromise between ...

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