Hospital-Based Medicine

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

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[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].

This study aims to address the limitations in gesture recognition caused by the susceptibility of te...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

Multi-target neural network model of anxiolytic activity of chemical compounds using correlation convolution of multiple docking energy spectra.

Anxiety disorders are one of the most common mental health pathologies in the world. They require se...

MSA-MaxNet: Multi-Scale Attention Enhanced Multi-Axis Vision Transformer Network for Medical Image Segmentation.

Convolutional neural networks (CNNs) are well established in handling local features in visual tasks...

Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently compli...

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL).

In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) ...

Inferring tumor purity using multi-omics data based on a uniform machine learning framework MoTP.

Existing algorithms for assessing tumor purity are limited to a single omics data, such as gene expr...

A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction.

Artificial intelligence (AI)-based multi-modal fusion algorithms are pivotal in emulating clinical p...

A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra.

The accuracy of assigning fluorophore identity and abundance, known as spectral unmixing, in biologi...

Dual-stage optimizer for systematic overestimation adjustment applied to multi-objective genetic algorithms for biomarker selection.

The selection of biomarker panels in omics data, challenged by numerous molecular features and limit...

Automated segmentation of brain metastases with deep learning: A multi-center, randomized crossover, multi-reader evaluation study.

BACKGROUND: Artificial intelligence has been proposed for brain metastasis (BM) segmentation but it ...

Recent Progress in the Physical Principles of Dynamic Ground Self-Righting.

Animals and robots must self-right on the ground after overturning. Biology research has described v...

A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.

Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biologi...

Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity.

Stratification of patients diagnosed with cancer has become a major goal in personalized oncology. O...

MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning.

MOTIVATION: Effective molecular representation is critical in drug development. The complex nature o...

[Detection model of atrial fibrillation based on multi-branch and multi-scale convolutional networks].

Atrial fibrillation (AF) is a life-threatening heart condition, and its early detection and treatmen...

Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early ...

Multi-Objective Performance Optimization of Machine Learning Models in Healthcare.

Multi-objective optimization holds particular significance for medical applications, wherein enhanci...

An Overview of Explainable AI Studies in the Prediction of Sepsis Onset and Sepsis Mortality.

Explainable artificial intelligence (AI) focuses on developing models and algorithms that provide tr...

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