Critical Care

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

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Subcategories: Sepsis
Showing 3655-3675 of 7,482 articles
Score-Based Diffusion Models With Self-Supervised Learning for Accelerated 3D Multi-Contrast Cardiac MR Imaging.

Long scan time significantly hinders the widespread applications of three-dimensional multi-contrast...

Hierarchical Multi-Class Group Correlation Learning Network for Medical Image Segmentation.

Hierarchical approaches have been tremendously successful at multi-label segmentation. However, it h...

MSMTSeg: Multi-Stained Multi-Tissue Segmentation of Kidney Histology Images via Generative Self-Supervised Meta-Learning Framework.

Accurately diagnosing chronic kidney disease requires pathologists to assess the structure of multip...

Multi-Gate Mixture of Multi-View Graph Contrastive Learning on Electronic Health Record.

Electronic Health Record (EHR) is the digital form of patient visits that contains various medical d...

MLOmics: Cancer Multi-Omics Database for Machine Learning.

Framing the investigation of diverse cancers as a machine learning problem has recently shown signif...

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue t...

A deep learning model for prediction of lysine crotonylation sites by fusing multi-features based on multi-head self-attention mechanism.

Lysine crotonylation (Kcr) is an important post-translational modification, which is present in both...

scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links.

Recent advancements in single-cell technologies have enabled comprehensive characterization of cellu...

GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.

Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced sur...

Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise...

Application of AI-assisted multi-advisor system combined with BOPPPS teaching model in clinical pharmacy education.

BACKGROUND: The development of clinical pharmacy in China has been relatively slow, and standardized...

ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning.

BACKGROUND: Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered out...

Multi-Knowledge Graph and Multi-View Entity Feature Learning for Predicting Drug-Related Side Effects.

Computational prediction of potential drug side effects plays a crucial role in reducing health risk...

Explainable deep learning for age and gender estimation in dental CBCT scans using attention mechanisms and multi task learning.

Accurate and interpretable age estimation and gender classification are essential in forensic and cl...

Diagnostic accuracy of artificial intelligence-based multi-spectrum analysis for molecular fingerprint detection of SARS-CoV-2.

Reverse transcription-polymerase chain reaction (RT-PCR) is the reference standard for COVID-19 diag...

Multi-view contrastive learning and symptom extraction insights for medical report generation.

The task of generating medical reports automatically is of paramount importance in modern healthcare...

Relationship between medication regimen complexity and pharmacist engagement in fluid stewardship.

PURPOSE: The medication regimen complexity intensive care unit (MRC-ICU) score has previously been a...

Bio inspired feature selection and graph learning for sepsis risk stratification.

Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accu...

Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction.

The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and pro...

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