Hospital-Based Medicine

Intensivists

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

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Identifying multi-functional bioactive peptide functions using multi-label deep learning.

The bioactive peptide has wide functions, such as lowering blood glucose levels and reducing inflamm...

circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.

Circular RNAs (circRNAs) generally bind to RNA-binding proteins (RBPs) to play an important role in ...

Entity recognition of Chinese medical text based on multi-head self-attention combined with BILSTM-CRF.

Named entities are the main carriers of relevant medical knowledge in Electronic Medical Records (EM...

Connecting artificial intelligence and primary care challenges: findings from a multi stakeholder collaborative consultation.

UNLABELLED: Despite widespread advancements in and envisioned uses for artificial intelligence (AI),...

[Predicting prolonged length of intensive care unit stay machine learning].

OBJECTIVE: To construct length of intensive care unit (ICU) stay (LOS-ICU) prediction models for ICU...

Advances in artificial intelligence and deep learning systems in ICU-related acute kidney injury.

PURPOSE OF REVIEW: Acute kidney injury (AKI) affects nearly 60% of all patients admitted to ICUs. La...

PSSP-MVIRT: peptide secondary structure prediction based on a multi-view deep learning architecture.

The prediction of peptide secondary structures is fundamentally important to reveal the functional m...

An Interpretable Intensive Care Unit Mortality Risk Calculator.

Mortality risk is a major concern to patients who have just been discharged from the intensive care ...

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.

Neuropsychiatric disorders such as schizophrenia are very heterogeneous in nature and typically diag...

MSF-GAN: Multi-Scale Fuzzy Generative Adversarial Network for Breast Ultrasound Image Segmentation.

Automatic breast ultrasound image (BUS) segmentation is still a challenging task due to poor image q...

EMS-Net: Enhanced Multi-Scale Network for Polyp Segmentation.

In recent years, polyp segmentation plays an important role in the diagnosis and treatment of colore...

Multi-Scale Aggregated-Dilation Network for ex-vivo Lung Cancer Detection with Fluorescence Lifetime Imaging Endomicroscopy.

Multi-scale architectures at a granular level are characterised by separating input features into gr...

Surgical instrument segmentation based on multi-scale and multi-level feature network.

Surgical instrument segmentation is critical for the field of computer-aided surgery system. Most of...

Exploring Features Contributing to the Early Prediction of Sepsis Using Machine Learning.

The increasing availability of electronic health records and administrative data and the adoption of...

Perioperative Risk Assessment in Pancreatic Surgery Using Machine Learning.

Pancreatic surgery is associated with a high risk for postoperative complications and death of patie...

A Machine Learning Understanding of Sepsis.

Sepsis is a serious cause of morbidity and mortality and yet its pathophysiology remains elusive. Re...

Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolutional Neural Networks.

Large annotated lung sound databases are publicly available and might be used to train algorithms fo...

Autonomous Systems and Artificial Intelligence - Hype or Prerequisite for P5 Medicine?

For meeting the challenge of aging, multi-diseased societies, cost containment, workforce developmen...

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