Critical Care

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

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Subcategories: Sepsis
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A Hybrid Rule-Based and Deep Learning Framework for Ventilator Waveform Segmentation and Delineation

Accurate assessment of patient-ventilator interaction is critical for optimizing respiratory support...

Developing a multi-domain EHR foundation model for predicting Hepatitis B liver disease: a clinical perspective

Foundation models trained on patient electronic health records (EHRs) hold promise for transforming ...

Deep Learning Decodes Latent ECG Signatures of Stress Cardiomyopathy

Background Stress cardiomyopathy (SCM) shares features with acute myocardial infarction (AMI) which ...

Clinical and Cross-Domain Validation of an LLM-Guided, Literature-Based Gene Prioritization Framework

Background: We previously published a literature based pipeline for sepsis gene prioritization (PS3 ...

PC-MCL: Patient-Consistent Multi-Cycle Learning with multi-label bias correction for respiratory sound classification

Automated respiratory sound classification supports the diagnosis of pulmonary diseases. However, ma...

AI-Powered Acoustic Surveillance for Early Detection of Calf Respiratory Disease

Effective management of Bovine Respiratory Disease Complex (BRDC) requires timely, non-invasive diag...

Coarse-to-Fine Non-rigid Multi-modal Image Registration for Historical Panel Paintings based on Crack Structures

Art technological investigations of historical panel paintings rely on acquiring multi-modal image d...

Skywork UniPic 3.0: Unified Multi-Image Composition via Sequence Modeling

The recent surge in popularity of Nano-Banana and Seedream 4.0 underscores the community's strong in...

Attention-Based Offline Reinforcement Learning and Clustering for Interpretable Sepsis Treatment

Sepsis remains one of the leading causes of mortality in intensive care units, where timely and accu...

Automated Assessment of OSCE Physical Exams using Multimodal AI

Background The assessment of physical examination skills in medical education is resource-intensive ...

LeMoF: Level-guided Multimodal Fusion for Heterogeneous Clinical Data

Multimodal clinical prediction is widely used to integrate heterogeneous data such as Electronic Hea...

EvoMorph: Counterfactual Explanations for Continuous Time-Series Extrinsic Regression Applied to Photoplethysmography

Wearable devices enable continuous, population-scale monitoring of physiological signals, such as ph...

Prediction of peripheral blood lymphocyte subpopulations after renal transplantation.

Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). ...

Dec 2025 40369954
An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis

The labor-intensive nature of medical data annotation presents a significant challenge for respira...

ViLU: Learning Vision-Language Uncertainties for Failure Prediction

Reliable Uncertainty Quantification (UQ) and failure prediction remain open challenges for Vision-...

ViLU: Learning Vision-Language Uncertainties for Failure Prediction

Reliable Uncertainty Quantification (UQ) and failure prediction remain open challenges for Vision-...

Stable-Hair v2: Real-World Hair Transfer via Multiple-View Diffusion Model

While diffusion-based methods have shown impressive capabilities in capturing diverse and complex ...

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