Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Deep learning and optimization enabled multi-objective for task scheduling in cloud computing.

In cloud computing (CC), task scheduling allocates the task to best suitable resource for execution....

MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation.

Automated segmentation algorithms for dermoscopic images serve as effective tools that assist dermat...

Finite-time cluster synchronization of multi-weighted fractional-order coupled neural networks with and without impulsive effects.

In this paper, finite-time cluster synchronization (FTCS) of multi-weighted fractional-order neural ...

Prediction of sepsis mortality in ICU patients using machine learning methods.

PROBLEM: Sepsis, a life-threatening condition, accounts for the deaths of millions of people worldwi...

Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.

Novel artificial intelligence methods can aide in identification of cases of conditions using only u...

Early sepsis mortality prediction model based on interpretable machine learning approach: development and validation study.

Sepsis triggers a harmful immune response due to infection, causing high mortality. Predicting sepsi...

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

The causes of traffic violations by elderly drivers are different from those of other age groups. To...

Machine Learning Tools for Acute Respiratory Distress Syndrome Detection and Prediction.

Machine learning (ML) tools for acute respiratory distress syndrome (ARDS) detection and prediction ...

Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis.

Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among c...

Prediction of 30-day mortality for ICU patients with Sepsis-3.

BACKGROUND: There is a growing demand for advanced methods to improve the understanding and predicti...

Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning.

BACKGROUND: Invasive Escherichia coli disease (IED), also known as invasive extraintestinal pathogen...

An Edge-Cloud-Aided Private High-Order Fuzzy C-Means Clustering Algorithm in Smart Healthcare.

Smart healthcare has emerged to provide healthcare services using data analysis techniques. Especial...

A Multi-Classification Accessment Framework for Reproducible Evaluation of Multimodal Learning in Alzheimer's Disease.

Multimodal learning is widely used in automated early diagnosis of Alzheimer's disease. However, the...

Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation-based clinical cases.

BACKGROUND: As generative artificial intelligence (GenAI) tools continue advancing, rigorous evaluat...

Research into the Applications of a Multi-Scale Feature Fusion Model in the Recognition of Abnormal Human Behavior.

Due to the increasing severity of aging populations in modern society, the accurate and timely ident...

Fusing multi-scale functional connectivity patterns via Multi-Branch Vision Transformer (MB-ViT) for macaque brain age prediction.

Brain age (BA) is defined as a measure of brain maturity and could help characterize both the typica...

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.

Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is ...

MSRA-Net: multi-channel semantic-aware and residual attention mechanism network for unsupervised 3D image registration.

. Convolutional neural network (CNN) is developing rapidly in the field of medical image registratio...

Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.

Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with significant ...

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