Intensivists

Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked t...

Mechanical performance dataset for alloy with applications at low temperatures.

Modern technologies such as liquid fuels (hydrogen, oxygen), superconductivity, and quantum technolo...

Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study.

BACKGROUND: The current Surviving Sepsis Campaign (SSC) guidelines provide recommendations on timing...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcom...

Accelerated brain magnetic resonance imaging with deep learning reconstruction: a comparative study on image quality in pediatric neuroimaging.

BACKGROUND: Magnetic resonance imaging (MRI) is crucial in pediatric radiology; however, the prolong...

SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction.

BACKGROUND: Sepsis is a life-threatening condition that is one of the major causes of death worldwid...

FCRNet: Fast Fourier convolutional residual network for ventilator bearing fault diagnosis.

This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosi...

EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation.

BACKGROUND: Drug recommendation is a crucial application of artificial intelligence in medical pract...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understandin...

A Multi-Scale attention network for building extraction from high-resolution remote sensing images.

The information in remote sensing images often leads to incomplete building contours and suboptimal ...

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors ...

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes.

Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinic...

Early prediction of non-invasive ventilation outcome using the TabPFN machine learning model: a multi-centre validation study.

Dataset of apples for grading by sweetness, ripeness and variety.

The study created a detailed database for apple quality inspection using a cost-effective, self-desi...

Exploring single-head and multi-head CNN and LSTM-based models for road surface classification using on-board vehicle multi-IMU data.

Accurate road surface monitoring is essential for ensuring vehicle and pedestrian safety, and it rel...

An interpretable dynamic ensemble selection multiclass imbalance approach with ensemble imbalance learning for predicting road crash injury severity.

Accurate prediction of crash injury severity and understanding the seriousness of multi-classificati...

Hyperbolic multi-channel hypergraph convolutional neural network based on multilayer hypergraph.

In recent years, hypergraph neural networks have achieved remarkable success in tasks such as node c...

Machine learning-driven programmed cell death signature for prognosis and drug candidate discovery in diffuse large B-cell lymphoma: Multi-cohort study and experimental validation.

BACKGROUND: Relapse and drug resistance are major contributor to chemotherapy failure in diffuse lar...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opport...

Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment.

This study presents a novel clinical decision support platform for orthodontic-orthognathic treatmen...

Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets.

The treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as...