Hospital-Based Medicine

Intensivists

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

6,181 articles
Stay Ahead - Weekly Intensivists research updates
Subscribe
Browse Categories
Showing 2710-2730 of 6,181 articles
Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.

Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric ca...

[Intelligent rehabilitation platform in intensive care unit].

As the development of rehabilitation medicine and critical care medicine, intensive care rehabilitat...

ncRNALocate-EL: a multi-label ncRNA subcellular locality prediction model based on ensemble learning.

Subcellular localizations of ncRNAs are associated with specific functions. Currently, an increasing...

Multi-modality imaging in aortic stenosis: an EACVI clinical consensus document.

In this EACVI clinical scientific update, we will explore the current use of multi-modality imaging ...

dm-GAN: Distributed multi-latent code inversion enhanced GAN for fast and accurate breast X-ray image automatic generation.

Breast cancer seriously threatens women's physical and mental health. Mammography is one of the most...

The Role of Vitamin D Binding Protein and Vitamin D Level in Mortality of Sepsis Patients.

BACKGROUND: Vitamin D plays crucial roles in immune cell function, including macrophage activation, ...

Optimal design of triangular side orifice using multi-objective optimization NSGA-II.

Triangular orifices are widely used in industrial and engineering applications, including fluid mete...

Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting.

Background Most artificial intelligence algorithms that interpret chest radiographs are restricted t...

ExpertNet: A Deep Learning Approach to Combined Risk Modeling and Subtyping in Intensive Care Units.

Risk models play a crucial role in disease prevention, particularly in intensive care units (ICUs). ...

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers.

Background Clinicians consider both imaging and nonimaging data when diagnosing diseases; however, c...

MVML-MPI: Multi-View Multi-Label Learning for Metabolic Pathway Inference.

Development of robust and effective strategies for synthesizing new compounds, drug targeting and co...

Multimodal deep learning approaches for single-cell multi-omics data integration.

Integrating single-cell multi-omics data is a challenging task that has led to new insights into com...

Machine learning for image-based multi-omics analysis of leaf veins.

Veins are a critical component of the plant growth and development system, playing an integral role ...

An Exploratory Multi-Session Study of Learning High-Dimensional Body-Machine Interfacing for Assistive Robot Control.

Individuals who suffer from severe paralysis often lose the capacity to perform fundamental body mov...

Narrowing the gap: expected versus deployment performance.

OBJECTIVES: Successful model development requires both an accurate a priori understanding of future ...

FGCNSurv: dually fused graph convolutional network for multi-omics survival prediction.

MOTIVATION: Survival analysis is an important tool for modeling time-to-event data, e.g. to predict ...

Predicting the risk of mortality in ICU patients based on dynamic graph attention network of patient similarity.

Predicting the risk of mortality of hospitalized patients in the ICU is essential for timely identif...

MCFF-MTDDI: multi-channel feature fusion for multi-typed drug-drug interaction prediction.

Adverse drug-drug interactions (DDIs) have become an increasingly serious problem in the medical and...

MMSMAPlus: a multi-view multi-scale multi-attention embedding model for protein function prediction.

Protein is the most important component in organisms and plays an indispensable role in life activit...

Browse Categories