Public Health & Policy

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk of osteoporosis-related fractures. Accurate identification and surveillance of patient populations with fractures has a significant impact on reduction of cost of care by preventing future fractures and its corresponding complications.

Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied to the relationship between diseases. The study aim was to identify diseases associated with endometriosis by applying RS based on item similarities to insurance data in South Korea. Women aged 15 to 45 years extracted from the Korean Health Insuranc...

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respira...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form requires monitoring and repeat serological and molec...

Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.

BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health ...

Chief complaint classification with recurrent neural networks.

Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automate...

Drivers for the development of an Animal Health Surveillance Ontology (AHSO).

Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems whe...

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions.

IMPORTANCE: Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk.

Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.

Ankle fractures are common orthopedic injuries with favorable outcomes when managed with open reduction and internal fixation (ORIF). Several patient-...

Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations.

BACKGROUND: The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, socia...

Lung Cancer Survival Prediction via Machine Learning Regression, Classification, and Statistical Techniques.

A regression model is developed to predict survival time in months for lung cancer patients. It was previously shown that predictive models perform ac...

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity.

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules induces the prolongation of the QT interval which leads to fatal ca...

Artificial Neural Network for in-Bed Posture Classification Using Bed-Sheet Pressure Sensors.

Pressure ulcer prevention is a vital procedure for patients undergoing long-term hospitalization. A human body lying posture (HBLP) monitoring system ...

Statistical outbreak detection by joining medical records and pathogen similarity.

We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines p...

Semi-supervised learning to improve generalizability of risk prediction models.

The utility of a prediction model depends on its generalizability to patients drawn from different but related populations. We explored whether a semi...

Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Use of prescription opioids and problems of abuse and addiction have increased over the past decade. Claims-based studies have documented substantial ...

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal .

Nontyphoidal species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susce...

A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geog...

Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning.

Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to d...

Gallic Acid Potentiates the Antimicrobial Activity of Tulathromycin Against Two Key Bovine Respiratory Disease (BRD) Causing-Pathogens.

Bovine respiratory disease (BRD) is the most common infectious disease in dairy and beef cattle. It is associated with significant morbidity and morta...