Infection Control

Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

BACKGROUND: Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been developed on retrospective data, but prospective validation of readmission models is rare. To the best of our knowledge, none of these developed models have...

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.

Approximately 300 million people are afflicted with asthma around the world, with the estimated death rate of 250,000 cases, indicating the significance of this disease. If not treated, it can turn into a serious public health problem. The best method to treat asthma is to control it. Physicians recommend continuous monitoring on asthma symptoms and offering treatment preventive plans based on the...

Matched Learning for Optimizing Individualized Treatment Strategies Using Electronic Health Records.

Current guidelines for treatment decision making largely rely on data from randomized controlled trials (RCTs) studying average treatment effects. The...

Deep-learning-based out-of-hospital cardiac arrest prognostic system to predict clinical outcomes.

AIM: Out-of-hospital cardiac arrest (OHCA) is a major healthcare burden, and prognosis is critical in decision-making for treatment and the withdrawal...

Recursive neural networks in hospital bed occupancy forecasting.

BACKGROUND: Efficient planning of hospital bed usage is a necessary condition to minimize the hospital costs. In the presented work we deal with the p...

Predictors of in-hospital length of stay among cardiac patients: A machine learning approach.

OBJECTIVE: The In-hospital length of stay (LOS) is expected to increase as cardiovascular diseases complexity increases and the population ages. This ...

Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia.

Dementia is a neurological and cognitive condition that affects millions of people around the world. At any given time in the United Kingdom, 1 in 4 h...

Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developin...

A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients followi...

Hyponatremia Presenting with Recurrent Mania.

Primary psychogenic polydipsia (PPD) is a chronic, relapsing condition in which there is a disturbance in thirst control primarily due to an underlyin...

A combined modelling of fuzzy logic and Time-Driven Activity-based Costing (TDABC) for hospital services costing under uncertainty.

Hospital traditional cost accounting systems have inherent limitations that restrict their usefulness for measuring the exact cost of healthcare servi...

An original design of remote robot-assisted intubation system.

The success rate of pre-hospital endotracheal intubation (ETI) by paramedics is lower than physicians. We aimed to establish a remote robot-assisted i...

Molecular Genotyping of Species Isolated from Patients in Tehran, Iran, by Repetitive Element PCR Fingerprinting.

BACKGROUND & OBJECTIVE: is an opportunistic pathogen with high pathogenic and antibiotic-resistance potential and is also considered as one of the ma...

Design and Evaluation of a Motorized Robotic Bed Mover With Omnidirectional Mobility for Patient Transportation.

Patient transportation in hospitals faces many challenges, including the limited manpower, work-related injuries, and low efficiency of current bed pu...

Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning.

This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum using Raman spectroscopy combined with pattern recognition ...

Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.

Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients wit...

Predicting Hospital Readmission via Cost-Sensitive Deep Learning.

With increased use of electronic medical records (EMRs), data mining on medical data has great potential to improve the quality of hospital treatment ...

Overproduction of efflux pumps caused reduced susceptibility to carbapenem under consecutive imipenem-selected stress in .

PURPOSE: is an important pathogen in the nosocomial infections worldwide. Combining with carbapenemases, efflux pumps and outer membrane proteins (OM...

Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier.

Electronic health records (EHRs) contain critical information useful for clinical studies. Early assessment of patients' mortality in intensive care u...

Assessing the impact of PM on respiratory disease using artificial neural networks.

Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM can penetrate th...