Hospital-Based Medicine

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

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Multi-scale transformation and evolutionary factors of ecological security patterns in the Yangtze River Economic Belt.

Ecological security is vital for ecosystem sustainability and varies across scales. Macro-scale asse...

Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations.

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disorder, recognized as t...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

The kidney is a target organ for the dysregulated host response to infection that defines sepsis, an...

A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses.

Ventilation quality in summer layer houses is critical for heat stress prevention, production perfor...

Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI.

Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morpholog...

MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.

Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pi...

MT-RCAF: A Multi-Task Residual Cross Attention Framework for EEG-based emotion recognition and mood disorder detection.

BACKGROUND AND OBJECTIVE: Prolonged abnormal emotions can gradually evolve into mood disorders such ...

Intelligent Recognition of Goji Berry Pests Using CNN With Multi-Graphic-Occlusion Data Augmentation and Multiple Attention Fusion Mechanisms.

Goji berry is an important economic crop, yet pest infestations pose a significant threat to its yie...

A scalable machine learning multi-local regression framework for potential energy surface fitting across diverse chemical landscapes.

The accurate characterization of the potential energy surface (PES) is fundamental to understanding ...

Rapid diagnosis of lung cancer by multi-modal spectral data combined with deep learning.

Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer d...

spaLLM: enhancing spatial domain analysis in multi-omics data through large language model integration.

Spatial multi-omics technologies provide valuable data on gene expression from various omics in the ...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is ...

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Assessing multi-hazard susceptibility and understanding community insights are important for effecti...

MHS U-Net: Multi-scale hybrid subtraction network for medical image segmentation.

Medical image segmentation plays a critical role in modern clinical diagnosis. However, existing met...

Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-yea...

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data.

Acute Respiratory Distress Syndrome (ARDS), characterized by the rapid onset of respiratory failure ...

Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs.

Escherichia coli recovered from dogs with clinical conditions such as urinary tract infections are o...

Precision medicine applications in dilated cardiomyopathy: Advancing personalized care.

Dilated cardiomyopathy (DCM) is a prevalent cardiac disorder affecting 1 in 250-500 individuals, cha...

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