Public Health & Policy

The most cited and co-cited COVID-19 articles: Knowledge base for rehabilitation team members.

BACKGROUND: The COVID-19 outbreak pandemic is a situation without a tested action plan. Rehabilitati...

Artificial Intelligence and Medicine: History, Current State, and Forecasts for the Future.

This article traces the history of the development of artificial intelligence as a science that cons...

What is Machine Learning? A Primer for the Epidemiologist.

Machine learning is a branch of computer science that has the potential to transform epidemiologic s...

Medication Adherence and Stroke Prevention: What Real World Data Tells Us.

Medication adherence, by definition,(2) is "the extent to which a patient acts in accordance with th...

Prognostic models will be victims of their own success, unless….

Predictive analytics have begun to change the workflows of healthcare by giving insight into our fut...

A virus precipitation method for concentration & detection of avian influenza viruses from environmental water resources & its possible application in outbreak investigations.

BACKGROUND & OBJECTIVES: Avian influenza (AI) viruses have been a major cause of public health conce...

The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction.

We estimate the causal effects of acute fine particulate matter exposure on mortality, health care u...

Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery.

IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible fo...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories abo...

Learning epidemic threshold in complex networks by Convolutional Neural Network.

Deep learning has taken part in the competition since not long ago to learn and identify phase trans...

[An overview of validation methods based on the medical claims database].

Medical claims database is an important source of data for studying the characteristics, and burden ...

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improv...

Using Machine Learning to Integrate Socio-Behavioral Factors in Predicting Cardiovascular-Related Mortality Risk.

Cardiovascular disease is prevalent and associated with significant mortality rate. Robust lifetime ...

Development of Deep Learning Algorithm for Detection of Colorectal Cancer in EHR Data.

We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal canc...

Scoring Patient Fall Reports Using Quality Rubric and Machine Learning.

Patient falls, a subcategory of patient safety events, cause further harm and anxiety to patients in...

Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home...

A New Approach to Compare the Performance of Two Classification Methods of Causes of Death for Timely Surveillance in France.

Timely mortality surveillance in France is based on the monitoring of electronic death certificates ...

Demand Analysis and Function Design of Health Decision Support System in China.

In order to improve the level of health decision-making, based on health information resources and d...

Characterizing Subgroups of High-Need, High-Cost Patients Based on Their Clinical Conditions: a Machine Learning-Based Analysis of Medicaid Claims Data.

Artificial neural network-assisted Fourier transform infrared spectroscopy for differentiation of Salmonella serogroups and its application on epidemiological tracing of Salmonella Bovismorbificans outbreak isolates from fresh sprouts.

Salmonellae represent one of the most common bacterial infection reagents in both humans and animals...

Context matters: using reinforcement learning to develop human-readable, state-dependent outbreak response policies.

The number of all possible epidemics of a given infectious disease that could occur on a given lands...