Infection Control

Machine learning in the prediction of medical inpatient length of stay.

Length of stay (LOS) estimates are important for patients, doctors and hospital administrators. However, making accurate estimates of LOS can be difficult for medical patients. This review was conducted with the aim of identifying and assessing previous studies on the application of machine learning to the prediction of total hospital inpatient LOS for medical patients. A review of machine learnin...

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19.

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patie...

Susceptible-Infected-Removed Mathematical Model under Deep Learning in Hospital Infection Control of Novel Coronavirus Pneumonia.

OBJECTIVE: This research aimed to explore the application of a mathematical model based on deep learning in hospital infection control of novel corona...

Automated Diagnosis and Localization of Melanoma from Skin Histopathology Slides Using Deep Learning: A Multicenter Study.

In traditional hospital systems, diagnosis and localization of melanoma are the critical challenges for pathological analysis, treatment instructions,...

Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated ...

Simultaneous degradation of glucocorticoids and sterilization using bubbling corona discharge plasma based systems: A promising terminal water treatment facility for hospital wastewater.

Glucocorticoids (GCs) have drawn great concern due to their widespread contamination in the environment and application in treating patients with COVI...

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 sleep and/or early-morning awakenings. Hyperarousal is...

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 role in the formation of noradrenergic neuronal c...

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 treatment. No single echocardiographic method has been...

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 change to biomedical computing and intelligence heal...

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 displaced and non-displaced fractures using convolutional ...

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 world's healthcare systems at risk. The first step...

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) algorithm-based computed tomography (CT) images were inve...

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 economic crises are aggravated by strong societal ...

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 algorithms are usually designed for the diagnosis (i.e., f...

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 ultrasound images, which was used for the research on ...

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 and disability. However, due to the lack of labeled ...

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 from CT is therefore very important for correct d...

Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify th...

Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electron...