Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Reintubation Summation Calculation: A Predictive Score for Extubation Failure in Critically Ill Patients.

OBJECTIVE: To derive and validate a multivariate risk score for the prediction of respiratory failur...

A machine learning model for predicting deterioration of COVID-19 inpatients.

The COVID-19 pandemic has been spreading worldwide since December 2019, presenting an urgent threat ...

ISSMF: Integrated semantic and spatial information of multi-level features for automatic segmentation in prenatal ultrasound images.

As an effective way of routine prenatal diagnosis, ultrasound (US) imaging has been widely used rece...

Diagnosis of Esophageal Lesions by Multi-Classification and Segmentation Using an Improved Multi-Task Deep Learning Model.

It is challenging for endoscopists to accurately detect esophageal lesions during gastrointestinal e...

Early heart rate variability evaluation enables to predict ICU patients' outcome.

Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activ...

Predictive classification of Alzheimer's disease using brain imaging and genetic data.

For now, Alzheimer's disease (AD) is incurable. But if it can be diagnosed early, the correct treatm...

Prediction of prognosis in elderly patients with sepsis based on machine learning (random survival forest).

BACKGROUND: Elderly patients with sepsis have many comorbidities, and the clinical reaction is not o...

Mechanism Analysis and Self-Adaptive RBFNN Based Hybrid Soft Sensor Model in Energy Production Process: A Case Study.

Despite hard sensors can be easily used in various condition monitoring of energy production process...

Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy.

In this study, a novel deep learning-based methodology was investigated to predict breast cancer res...

A Multi-Task Learning Framework for Automated Segmentation and Classification of Breast Tumors From Ultrasound Images.

Breast cancer is one of the most fatal diseases leading to the death of several women across the wor...

Robust Ship Detection in Infrared Images through Multiscale Feature Extraction and Lightweight CNN.

The sophistication of ship detection technology in remote sensing images is insufficient, the detect...

Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition.

Recognizing multiple labels of an image is a practical yet challenging task, and remarkable progress...

Multi-Task Learning With Coarse Priors for Robust Part-Aware Person Re-Identification.

Part-level representations are important for robust person re-identification (ReID), but in practice...

Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic Data.

Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods r...

PDGNet: Predicting Disease Genes Using a Deep Neural Network With Multi-View Features.

The knowledge of phenotype-genotype associations is crucial for the understanding of disease mechani...

MDL-CPI: Multi-view deep learning model for compound-protein interaction prediction.

Elucidating the mechanisms of Compound-Protein Interactions (CPIs) plays an essential role in drug d...

Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury.

This study was aimed at analyzing the diagnostic value of convolutional neural network models on acc...

Multi-Modal Song Mood Detection with Deep Learning.

The production and consumption of music in the contemporary era results in big data generation and c...

Multi-Path U-Net Architecture for Cell and Colony-Forming Unit Image Segmentation.

U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In th...

Pulmonary nodules detection based on multi-scale attention networks.

Pulmonary nodules are the main manifestation of early lung cancer. Therefore, accurate detection of ...

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