Intensivists

ProgCAE: a deep learning-based method that integrates multi-omics data to predict cancer subtypes.

Determining cancer subtypes and estimating patient prognosis are crucial for cancer research. The ma...

[Intelligent intensive care unit makes medicine more accessible].

In the past half century, critical care medicine has made rapid development, and the survival rate o...

Heart Failure Assessment Using Multiparameter Polar Representations and Deep Learning.

Heart failure refers to the inability of the heart to pump enough amount of blood to the body. Nearl...

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics.

Combined functional-anatomic imaging modalities, which integrate the benefits of visualizing gross a...

A Pilot Study of Deep Learning Models for Camera based Hand Hygiene Monitoring in ICU.

Hand hygiene is key to preventing cross-infections in the Intensive Care Unit (ICU). Monitoring of h...

Predicting Dementia Risk for Elderly Community Dwellers in Primary Care Services Using Subgroup-specific Prediction Models.

Early detection of individuals with a high risk of dementia is crucial for prompt intervention and c...

Endovascular Tool Segmentation with Multi-lateral Branched Network during Robot-assisted Catheterization.

Robot-assisted catheterization is routinely carried out for intervention of cardiovascular diseases....

Real-Time-Capable Muscle Force Estimation for Monitoring Robotic Rehabilitation Therapy in the Intensive Care Unit.

In this paper, a method is proposed to enable real-time monitoring of muscle forces during robotic r...

[A method for photoplethysmography signal quality assessment fusing multi-class features with multi-scale series information].

Photoplethysmography (PPG) is often affected by interference, which could lead to incorrect judgment...

[Research on multi-class orthodontic image recognition system based on deep learning network model].

To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep le...

Are we ready to adapt artificial intelligence for early sepsis detection?

Deep learning-based multi-functional therapeutic peptides prediction with a multi-label focal dice loss function.

MOTIVATION: With the great number of peptide sequences produced in the postgenomic era, it is highly...

An interpretable machine learning model for real-time sepsis prediction based on basic physiological indicators.

OBJECTIVE: In view of the important role of risk prediction models in the clinical diagnosis and tre...

Artificial Intelligence for Early Sepsis Detection: A Word of Caution.

Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information.

Emerging studies have shown that circular RNAs (circRNAs) are involved in a variety of biological pr...

Auditory stimulation and deep learning predict awakening from coma after cardiac arrest.

Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. ...

Attention-guided multi-scale deep object detection framework for lymphocyte analysis in IHC histological images.

Tumor-infiltrating lymphocytes are specialized lymphocytes that can detect and kill cancerous cells....

AFTGAN: prediction of multi-type PPI based on attention free transformer and graph attention network.

MOTIVATION: Protein-protein interaction (PPI) networks and transcriptional regulatory networks are c...

DrugAI: a multi-view deep learning model for predicting drug-target activating/inhibiting mechanisms.

Understanding the mechanisms of candidate drugs play an important role in drug discovery. The activa...

Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning.

Differentiating cancer subtypes is crucial to guide personalized treatment and improve the prognosis...

Adaptive risk-aware sharable and individual subspace learning for cancer survival analysis with multi-modality data.

Biomedical multi-modality data (also named multi-omics data) refer to data that span different types...