Hospital-Based Medicine

Intensivists

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

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An Integrated Fuzzy Neural Network and Topological Data Analysis for Molecular Graph Representation Learning and Property Forecasting.

Within a recent decade, graph neural network (GNN) has emerged as a powerful neural architecture for...

An Attention-Based Deep Neural Network Model to Detect Cis-Regulatory Elements at the Single-Cell Level From Multi-Omics Data.

Cis-regulatory elements (cREs) play a crucial role in regulating gene expression and determining cel...

χ-sepnet: Deep Neural Network for Magnetic Susceptibility Source Separation.

Magnetic susceptibility source separation (χ-separation), an advanced quantitative susceptibility ma...

Identification of DNA damage repair-related genes in sepsis using bioinformatics and machine learning: An observational study.

Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanis...

iMFP-LG: Identify Novel Multi-functional Peptides Using Protein Language Models and Graph-based Deep Learning.

Functional peptides are short amino acid fragments that have a wide range of beneficial functions fo...

Relative Value Encoding in Large Language Models: A Multi-Task, Multi-Model Investigation.

In-context learning enables large language models (LLMs) to perform a variety of tasks, including so...

AI-driven multi-omics profiling of sepsis immunity in the digestive system.

Sepsis is a life-threatening systemic inflammatory syndrome characterized by a complex immune biphas...

Identifying Common Diagnostic Biomarkers and Therapeutic Targets between COPD and Sepsis: A Bioinformatics and Machine Learning Approach.

BACKGROUND: Evidence suggests a bidirectional association between chronic obstructive pulmonary dise...

Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm.

Facing the problems of large-scale rapid and disorderly loading, the robotic arm has the problems of...

A deep learning-based algorithm for the detection of personal protective equipment.

Personal protective equipment (PPE) is critical for ensuring the safety of construction workers. How...

Rice disease detection method based on multi-scale dynamic feature fusion.

In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, an...

Interpretable AI-driven multi-objective risk prediction in heart failure patients with thyroid dysfunction.

INTRODUCTION: Heart Failure (HF) complicated by thyroid dysfunction presents a complex clinical chal...

A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction.

Hyperspectral Image (HSI) classification tasks are usually impacted by Convolutional Neural Networks...

Classification of fashion e-commerce products using ResNet-BERT multi-modal deep learning and transfer learning optimization.

As the fashion e-commerce markets rapidly develop, tens of thousands of products are registered dail...

Real estate valuation with multi-source image fusion and enhanced machine learning pipeline.

The automated valuation model (AVM) has been widely used by real estate stakeholders to provide accu...

A criterion for assessing obstacle-induced environmental complexity in multi-robot coverage exploration.

In many applications, such as coverage exploration and search and rescue missions, accurately assess...

mGNN-bw: Multi-Scale Graph Neural Network Based on Biased Random Walk Path Aggregation for ASD Diagnosis.

In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) a...

A Topology-Enhanced Multi-Viewed Contrastive Approach for Molecular Graph Representation Learning and Classification.

In recent times, graph representation learning has been becoming a hot research topic which has attr...

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