Hospital-Based Medicine

Intensivists

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

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Evaluation of sports training methods and technical characteristics based on multi-dimensional driving fuzzy intelligent computing.

To improve the competitive state of badminton athletes and summarize the technical characteristics o...

DeepCR: predicting cytokine receptor proteins through pretrained language models and deep learning networks.

Cytokine receptors play a pivotal role in mediating the immune response and are critical in cytokine...

Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requirin...

Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.

OBJECTIVE: This study aimed to construct a novel model, Multi-Spatial Attention U-Net (MSAU-Net) by ...

Multi-Omics-Based Characterization of DNA Methylation Episignatures for Papillary Thyroid Cancer in a Chinese Population.

Thyroid cancer is the most common endocrine malignancy, with papillary thyroid cancer (PTC) account...

AMDCnet: attention-gate-based multi-scale decomposition and collaboration network for long-term time series forecasting.

INTRODUCTION: Time series analysis plays a critical role in various applications, including sensor d...

Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis.

Sepsis is a systemic inflammatory response syndrome that predisposes to severe lung infections (SeAL...

Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.

Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug res...

A cell-interacting and multi-correcting method for automatic circulating tumor cells detection.

Sensitive detection of circulating tumor cells (CTCs) from peripheral blood can serve as an effectiv...

Multi-Scale Vision Transformer with Optimized Feature Fusion for Mammographic Breast Cancer Classification.

: Breast cancer remains one of the leading causes of mortality among women worldwide, highlighting t...

Role of multi-omics in aquaculture genetics and breeding: current status and future perspective.

Aquaculture, a fast-growing sector, plays an important role in the supply of nutrient-rich food for ...

Impact of analytical bias on machine learning models for sepsis prediction using laboratory data.

OBJECTIVES: Machine learning (ML) models, using laboratory data, support early sepsis prediction. Ho...

Advanced predictive modeling for enhanced mortality prediction in ICU stroke patients using clinical data.

Background Stroke is second-leading cause of disability and death among adults. Approximately 17 mil...

MOAL: Multi-view Out-of-distribution Awareness Learning.

Multi-view learning integrates data from multiple sources to enhance task performance by improving d...

AI-assisted multi-OMICS analysis reveals new markers for the prediction of AD.

Alzheimer's Disease (AD) is the most prevalent neurodegenerative disorder, characterized by progress...

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through...

MultiV_Nm: a prediction method for 2'-O-methylation sites based on multi-view features.

As a crucial class of chemical modifications, 2'-O-methylation modification (abbreviated as Nm) is w...

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) faci...

Discovery of multi-metal-layered double hydroxides for decontamination of iodate by machine learning-assisted experiments.

The development of novel materials for radioactive iodate adsorption is critical for nuclear waste m...

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