Critical Care

Towards real-time diagnosis for pediatric sepsis using graph neural network and ensemble methods.

OBJECTIVE: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Timely diagnosis and intervention are essential to curing sepsis, but there is a lack of research on the prediction of sepsis at shorter time intervals. This study proposes a predictive model towards real-time diagnosis of sepsis to help reduce the time ...

Predicting ventilator-associated pneumonia with machine learning.

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifying VAP display low accuracy, and their use may delay antimicrobial therapy. VAP diagnostics derived from machine learning (ML) methods that utilize electronic health record (EHR) data have not yet been explored. The objective of this study is to comp...

Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center Dataset.

OBJECTIVES: Develop, as a proof of concept, a recurrent neural network model using electronic medical records data capable of continuously assessing a...

MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.

The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association with various human diseases. It is desirable to buil...

RNA-binding protein recognition based on multi-view deep feature and multi-label learning.

RNA-binding protein (RBP) is a class of proteins that bind to and accompany RNAs in regulating biological processes. An RBP may have multiple target R...

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis...

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2....

Avoidable Serum Potassium Testing in the Cardiac ICU: Development and Testing of a Machine-Learning Model.

OBJECTIVES: To create a machine-learning model identifying potentially avoidable blood draws for serum potassium among pediatric patients following ca...

[A Case of Descending Colon and Rectal Cancer with Acute Myeloid Leukemia Performed Robot‒Assisted Hartmann's Procedure].

The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rectal cancer surgery, was referred to our hospital fo...

A machine-learning based approach to quantify fine crackles in the diagnosis of interstitial pneumonia: A proof-of-concept study.

Fine crackles are frequently heard in patients with interstitial lung diseases (ILDs) and are known as the sensitive indicator for ILDs, although the ...

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning.

With the biomedical field generating large quantities of time series data, there has been a growing interest in developing and refining machine learni...

Artificial intelligence-based prediction of transfusion in the intensive care unit in patients with gastrointestinal bleeding.

OBJECTIVE: Gastrointestinal (GI) bleeding commonly requires intensive care unit (ICU) in cases of potentialhaemodynamiccompromise or likely urgent int...

A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients.

Deep venous thrombosis (DVT) is associated with significant morbidity, mortality, and increased healthcare costs. Standard scoring systems for DVT ris...

Deep learning supported disease detection with multi-modality image fusion.

Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing adequate complementary information from multi-mod...

Natural Language Processing Performance for the Identification of Venous Thromboembolism in an Integrated Healthcare System.

Real-time identification of venous thromboembolism (VTE), defined as deep vein thrombosis (DVT) and pulmonary embolism (PE), can inform a healthcare o...

High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria.

Changes to mitochondrial architecture are associated with various adaptive and pathogenic processes. However, quantification of changes to mitochondri...

Achieving Equitable Access to Medicines and Health Services: A COVID-19-time Recalled Matter.

In the 21 century, while some people seek to use artificial intelligence for health services delivery, others have to surrender their health rights to...

Cytomegalovirus and Severe Acute Respiratory Syndrome Coronavirus 2 Co-infection in Renal Transplants: A Retrospective Study from a Single Center.

There is a scarcity of data regarding the impact of cytomegalovirus (CMV) infection complicating the coronavirus disease-2019 (COVID-19) course. The o...

Effect of Ramadan Fasting on Chronic Inflammation and Body Composition in Patients with Chronic Kidney Disease.

Chronic kidney disease (CKD) is associated with a state of chronic inflammation which is responsible for many of the pathophysiological changes detect...

End-stage renal disease at dialysis initiation: Epidemiology and mortality risks during the first year of hemodialysis.

Chronic kidney disease (CKD) treated by hemodialysis (HD) is a worldwide major public health problem. Its incidence is getting higher and higher, lead...