Critical Care

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

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Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis.

The automatic diagnosis of various retinal diseases from fundus images is important to support clini...

A machine learning-based clinical tool for diagnosing myopathy using multi-cohort microarray expression profiles.

BACKGROUND: Myopathies are a heterogenous collection of disorders characterized by dysfunction of sk...

Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records.

BACKGROUND: Application of Artificial Intelligence (AI) and the use of agent-based systems in the he...

"Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images".

Coronavirus disease 2019 (COVID-19) is a novel harmful respiratory disease that has rapidly spread w...

A Customizable Analysis Flow in Integrative Multi-Omics.

The number of researchers using multi-omics is growing. Though still expensive, every year it is che...

Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning.

Predicting compounds with single- and multi-target activity and exploring origins of compound specif...

Machine learning algorithm for early detection of end-stage renal disease.

BACKGROUND: End stage renal disease (ESRD) describes the most severe stage of chronic kidney disease...

Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). How...

Peritoneal dialysis: An effective therapeutic modality in acute kidney injury.

BACKGROUND: Peritoneal dialysis (PD) as a modality of renal replacement therapy (RRT) in acute kidne...

Intravenous iron therapy and the cardiovascular system: risks and benefits.

Anaemia is a common complication of chronic kidney disease (CKD). In this setting, iron deficiency i...

Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic ...

A Methodology Based on Expert Systems for the Early Detection and Prevention of Hypoxemic Clinical Cases.

Respiratory diseases are currently considered to be amongst the most frequent causes of death and di...

Automated estimation of echocardiogram image quality in hospitalized patients.

We developed a machine learning model for efficient analysis of echocardiographic image quality in h...

Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks.

BACKGROUND: The identification of early mild cognitive impairment (EMCI), which is an early stage of...

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma...

Multi-task convolutional neural network-based design of radio frequency pulse and the accompanying gradients for magnetic resonance imaging.

Modern MRI systems usually load the predesigned RFs and the accompanying gradients during clinical s...

A deep learning framework for quality assessment and restoration in video endoscopy.

Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical tre...

Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning.

Rapid assessment of breathing patterns is important for several emergency medical situations. In thi...

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome.

Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute r...

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