Critical Care

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

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Multi-Level Ethical Considerations of Artificial Intelligence Health Monitoring for People Living with Parkinson's Disease.

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI...

A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas.

BACKGROUND: The anatomical infiltrated brain area and the boundaries of gliomas have a significant i...

Multi-scale feature selection network for lightweight image super-resolution.

Recently, many super-resolution (SR) methods based on convolutional neural networks (CNNs) have achi...

MLapRVFL: Protein sequence prediction based on Multi-Laplacian Regularized Random Vector Functional Link.

Protein sequence classification is a crucial research field in bioinformatics, playing a vital role ...

An event-triggered collaborative neurodynamic approach to distributed global optimization.

In this paper, we propose an event-triggered collaborative neurodynamic approach to distributed glob...

Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders.

Deep learning methods have gained significant attention in sleep science. This study aimed to assess...

Pressure support ventilation in intensive care patients receiving prolonged invasive ventilation.

To our knowledge, the use and management of pressure support ventilation (PSV) in patients receivin...

Temperature and haemodynamic effects of a 100 mL bolus of 20% albumin at room versus body temperature in cardiac surgery patients.

To study the temperature and haemodynamic effects of room versus body temperature 20% albumin fluid...

Chewing gum prophylaxis for postoperative nausea and vomiting in the intensive care unit: a pilot randomised controlled trial.

To test the effectiveness of chewing gum in the prophylaxis of postoperative nausea and vomiting (P...

A deep learning approach for inpatient length of stay and mortality prediction.

PURPOSE: Accurate prediction of the Length of Stay (LoS) and mortality in the Intensive Care Unit (I...

[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, ...

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images.

We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign d...

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a...

MicroRNA-30a inhibits cell proliferation in a sepsis-induced acute kidney injury model by targeting the YAP-TEAD complex.

BACKGROUND: Acute kidney injury (AKI) is a primary feature of renal complications in patients with s...

Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network.

Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a...

Molecular Joint Representation Learning via Multi-Modal Information of SMILES and Graphs.

In recent years, artificial intelligence has played an important role on accelerating the whole proc...

Identifying cancer risks using spectral subset feature selection based on multi-layer perception neural network for premature treatment.

Recently, human beings have been affected mainly by dreadful cancer diseases. Predicting cancer risk...

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