Hospital-Based Medicine

Intensivists

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

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Showing 358-378 of 6,135 articles
MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.

High-throughput multi-omic molecular profiling allows the probing of biological systems at unprecede...

Multi-scale conv-attention U-Net for medical image segmentation.

U-Net-based network structures are widely used in medical image segmentation. However, effectively c...

Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential the...

Revolutionizing Intensive Care Unit Care: A Scoping Review of Multimodal Family Engagement Technologies.

This scoping review systematically examines the emerging field of multimodal family engagement techn...

DruGagent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction.

Advancements in large language models (LLMs) allow them to address diverse questions using human-lik...

An innovative underdriven multi-degree-of-freedom sea turtle hydrofoil design.

This study presents a new design for a multi-degree-of-freedom underdriven mechanism. The aim is to ...

Multi-Scale Group Agent Attention-Based Graph Convolutional Decoding Networks for 2D Medical Image Segmentation.

Automated medical image segmentation plays a crucial role in assisting doctors in diagnosing disease...

SFM-Net: Semantic Feature-Based Multi-Stage Network for Unsupervised Image Registration.

It is difficult for general registration methods to establish the fine correspondence between images...

Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification.

In many challenging breast cancer pathology images, the proportion of truly informative tumor region...

Self-Supervised Multi-Scale Multi-Modal Graph Pool Transformer for Sellar Region Tumor Diagnosis.

The sellar region tumor is a brain tumor that only exists in the brain sellar, which affects the cen...

Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.

Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diag...

Artificial Intelligence for the Detection of Patient-Ventilator Asynchrony.

Patient-ventilator asynchrony (PVA) is a challenge to invasive mechanical ventilation characterized ...

Asymmetric Adaptive Heterogeneous Network for Multi-Modality Medical Image Segmentation.

Existing studies of multi-modality medical image segmentation tend to aggregate all modalities witho...

HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification.

Fine-grained classification of whole slide images (WSIs) is essential in precision oncology, enablin...

MT-CooL: Multi-Task Cooperative Learning via Flat Minima Searching.

While multi-task learning (MTL) has been widely developed for natural image analysis, its potential ...

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.

The COmmunicating Narrative Concerns Entered by RNs (CONCERN) early warning system (EWS) uses real-t...

Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks.

Chronic noncommunicable diseases (NCDS) are often characterized by gradual onset and slow progressio...

Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.

The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis a...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs a...

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