Public Health & Policy

Latest AI and machine learning research in public health & policy for healthcare professionals.

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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...

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...

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...

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 ...

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

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

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...

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 in...

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...

Non-Gaussian Methods for Causal Structure Learning.

Causal structure learning is one of the most exciting new topics in the fields of machine learning a...

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 patie...

Childhood Asthma: Advances Using Machine Learning and Mechanistic Studies.

A paradigm shift brought by the recognition that childhood asthma is an aggregated diagnosis that co...

Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications.

Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional f...

MIRKB: a myocardial infarction risk knowledge base.

Myocardial infarction (MI) is a common cardiovascular disease and a leading cause of death worldwide...

Real-time Epidemic Forecasting: Challenges and Opportunities.

Infectious disease outbreaks play an important role in global morbidity and mortality. Real-time epi...

Nursing and Rehabilitative Care of the Elderly Using Humanoid Robots.

Japan's declining birth rate and increasing aging population prompted intercessory efforts towards r...

Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning.

The creation of big clinical data cohorts for machine learning and data analysis require a number of...

Unhealthy Behaviors, Prevention Measures, and Neighborhood Cardiovascular Health: A Machine Learning Approach.

This study identifies and ranks predictors of cardiovascular health at the neighborhood level in the...

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