Critical Care

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

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Showing 1975-1995 of 7,427 articles
An implantable soft robotic ventilator augments inspiration in a pig model of respiratory insufficiency.

Severe diaphragm dysfunction can lead to respiratory failure and to the need for permanent mechanica...

Multi-task machine learning improves multi-seasonal prediction of the Indian Ocean Dipole.

As one of the most predominant interannual variabilities, the Indian Ocean Dipole (IOD) exerts great...

A multi-scale, multi-region and attention mechanism-based deep learning framework for prediction of grading in hepatocellular carcinoma.

BACKGROUND: Histopathological grading is a significant risk factor for postsurgical recurrence in he...

A multi-perspective information aggregation network for automated-staging detection of nasopharyngeal carcinoma.

Accurate-staging is important when planning personalized radiotherapy. However,-staging via manual s...

A Joint Group Sparsity-based deep learning for multi-contrast MRI reconstruction.

Multi-contrast magnetic resonance imaging (MRI) can provide richer diagnosis information. The data a...

Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of m...

Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms.

Earthquake is one of the natural disasters that have a big impact on society. Currently, there are m...

A Unified Multi-Phase CT Synthesis and Classification Framework for Kidney Cancer Diagnosis With Incomplete Data.

Multi-phase computed tomography (CT) is widely adopted for the diagnosis of kidney cancer due to the...

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection.

Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are...

Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs.

Background Supine chest radiography for bedridden patients in intensive care units (ICUs) is one of ...

Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.

Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record t...

Multi-dimensional feature recognition model based on capsule network for ubiquitination site prediction.

Ubiquitination is an important post-translational modification of proteins that regulates many cellu...

Long-distance dependency combined multi-hop graph neural networks for protein-protein interactions prediction.

BACKGROUND: Protein-protein interactions are widespread in biological systems and play an important ...

Prior Attention Network for Multi-Lesion Segmentation in Medical Images.

The accurate segmentation of multiple types of lesions from adjacent tissues in medical images is si...

Respiratory motion prediction based on deep artificial neural networks in CyberKnife system: A comparative study.

BACKGROUND: In external beam radiotherapy, a prediction model is required to compensate for the temp...

A Critical Review of Deep Learning-Based Multi-Sensor Fusion Techniques.

In this review, we provide a detailed coverage of multi-sensor fusion techniques that use RGB stereo...

Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series.

Tree-based machine learning methods have gained traction in the statistical and data science fields....

Passive tracking of underwater acoustic targets based on multi-beam LOFAR and deep learning.

Conventional passive tracking methods for underwater acoustic targets in sonar engineering generate ...

Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms.

Next basket recommendation is a critical task in market basket data analysis. It is particularly imp...

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