Critical Care

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

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Showing 2668-2688 of 7,452 articles
Machine Learning-Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review.

BACKGROUND: Timely identification of patients at a high risk of clinical deterioration is key to pri...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour.

Recently, coronary heart disease has attracted more and more attention, where segmentation and analy...

CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction.

Improving the accuracy of predicting protein crystallization is very important for protein crystalli...

Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer.

Pancreatic cancer is a malignant form of cancer with one of the worst prognoses. The poor prognosis ...

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

Digital reconstruction of neuronal structures is very important to neuroscience research. Many exist...

Improved Segmentation of the Intracranial and Ventricular Volumes in Populations with Cerebrovascular Lesions and Atrophy Using 3D CNNs.

Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importan...

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus,...

Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.

The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and V...

A Machine Learning Multi-Class Approach for Fall Detection Systems Based on Wearable Sensors with a Study on Sampling Rates Selection.

Falls are dangerous for the elderly, often causing serious injuries especially when the fallen perso...

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is ...

A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues.

Reliable counting of glomeruli and evaluation of glomerulosclerosis in renal specimens are essential...

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in -derived astrocytes ablated mice.

Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine...

Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases.

The mortality prediction of diverse rare diseases using electronic health record (EHR) data is a cru...

Neural Multi-Task Learning for Adverse Drug Reaction Extraction.

A reliable and searchable knowledge database of adverse drug reactions (ADRs) is highly important an...

A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation.

Deep learning models are increasingly studied in the field of critical care. However, due to the lac...

Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms.

The efficacy of early fluid treatment in patients with sepsis is unclear and may contribute to serio...

[Artificial intelligence in neurocritical care].

Artificial intelligence (AI) has been introduced into medicine and an AI-assisted medicine will be t...

A microfluidic robot for rare cell sorting based on machine vision identification and multi-step sorting strategy.

The identification, sorting and analysis of rare target single cells in human blood has always been ...

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