Infection Control

The effects of a sleep robot intervention on sleep, depression and anxiety in adults with insomnia - Study protocol of a randomized waitlist-controlled trial.

Insomnia is a common sleep disorder characterized by difficulties initiating sleep, maintaining slee...

Introducing Artificial Intelligence Applications at Our Community Hospital: A Contrarian Approach.

Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering.

BACKGROUND: We aimed to cluster patients with acute kidney injury at hospital admission into clinica...

Mutations of PHOX2B Gene in Patients of Obesity Hypoventilation Syndrome in Central India.

 Paired-like homeobox 2B (PHOX2B) gene on chromosome 4p12 codes for a transcription factor having a...

Machine Learning Models for Survival and Neurological Outcome Prediction of Out-of-Hospital Cardiac Arrest Patients.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a major health problem worldwide, and neurologi...

Automatic Assessment of Mitral Regurgitation Severity Using the Mask R-CNN Algorithm with Color Doppler Echocardiography Images.

Accurate assessment of mitral regurgitation (MR) severity is critical in clinical diagnosis and trea...

In-hospital Outcomes of Infective Endocarditis from 1978 to 2015: Analysis Through Machine-Learning Techniques.

BACKGROUND: Early identification of patients with infective endocarditis (IE) at higher risk for in-...

An Intelligent Control Model of Credit Line Computing in Intelligence Health-Care Systems.

Technologies such as machine learning and artificial intelligence have brought about a tremendous ch...

Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran.

This study was aimed to investigate the air pollutants impact on heart patient's hospital admission ...

Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmona...

External Validation of Deep Learning Algorithm for Detecting and Visualizing Femoral Neck Fracture Including Displaced and Non-displaced Fracture on Plain X-ray.

This study aimed to develop a method for detection of femoral neck fracture (FNF) including displace...

Deep Learning-Based Computed Tomography Image Features in the Detection and Diagnosis of Perianal Abscess Tissue.

The performance characteristics of deep learning fully convolutional neural network (DLFCNN) algorit...

Hybrid Deep-Learning and Machine-Learning Models for Predicting COVID-19.

The COVID-19 pandemic has had a significant impact on public life and health worldwide, putting the ...

Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors.

The COVID-19 pandemic continues to have a devastating impact on Brazil. Brazil's social, health and ...

A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia.

Atrial fibrillation (AF) is the most common cardiovascular disease (CVD), and most existing algorith...

Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia.

The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultr...

Predicting Recurrence for Patients With Ischemic Cerebrovascular Events Based on Process Discovery and Transfer Learning.

The recurrence of Ischemic cerebrovascular events (ICE) often results in a high rate of mortality an...

MSDS-UNet: A multi-scale deeply supervised 3D U-Net for automatic segmentation of lung tumor in CT.

Lung cancer is one of the most common and deadly malignant cancers. Accurate lung tumor segmentation...

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.

BACKGROUND: We performed this study to establish a prediction model for 1-year neurological outcomes...

Using machine learning to predict severe hypoglycaemia in hospital.

AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients...

Machine ​learning algorithms for claims data-based prediction of in-hospital mortality in patients with heart failure.

AIMS: Models predicting mortality in heart failure (HF) patients are often limited with regard to pe...