Public Health & Policy

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 concern. Wild migratory birds and contaminated environmental sources such as waterbodies soiled with bird droppings play a significant role in the transmission of AI viruses. The objective of the present study was to develop a sensitive and user-friendly method for the concentration and detection of AI v...

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 use, and medical costs among the US elderly using Medicare data. We instrument for air pollution using changes in local wind direction and develop a new approach that uses machine learning to estimate the life-years lost due to pollution exposure. Finally, we characterize treatment effect heterogenei...

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 for an estimated 40% to 55% of all health care costs...

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 about teens whose death from suicide was attributed t...

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 transitions in physical systems such as many-body quant...

[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 of diseases, to provide a basis for the developmen...

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improvement of the surveillance system for these disease...

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 risk stratification for cardiovascular disease is ...

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 cancer in Taiwanese adults. We collected data of 58152...

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 healthcare systems. Patient fall reports are a va...

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 health care (HHC) population. Existing standardiz...

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 to provide information to health authorities. This...

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 decision support function types, this study summari...

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. For detection and epidemiological elucidation of...

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 landscape is large for systems of real-world complexity...

Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges.

Combinations of healthcare claims data with additional datasets provide large and rich sources of information. The dimensionality and complexity of th...

Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic lymphoma kinase () mutation tests. To facilitate ...

Non-Gaussian Methods for Causal Structure Learning.

Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences includin...

Digital transformation in healthcare - architectures of present and future information technologies.

Healthcare providers all over the world are faced with a single challenge: the need to improve patient outcomes while containing costs. Drivers includ...