AIMC Topic: Population Surveillance
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Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.
Health informatics journal
Dec 27, 2017
The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease m...
Big Data in Public Health: Terminology, Machine Learning, and Privacy.
Annual review of public health
Dec 20, 2017
The digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores se...
Poor vitamin D status increases the risk of anemia in school children: National Food and Nutrition Surveillance.
Nutrition (Burbank, Los Angeles County, Calif.)
Oct 12, 2017
OBJECTIVES: This study aimed to investigate the association between 25-hydroxyvitamin D (25[OH]D) concentrations and the risk of anemia in a large cohort of children with consideration for the effects of sex, body mass index (BMI), serum intact parat...
Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population.
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Aug 29, 2017
PURPOSE: Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomati...
Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.
PloS one
Dec 9, 2016
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research w...
Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).
BMJ open
Mar 3, 2016
OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections ...
Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.
Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Jan 4, 2016
OBJECTIVE: Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identi...
Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance.
PLoS computational biology
Oct 29, 2015
We present a machine learning-based methodology capable of providing real-time ("nowcast") and forecast estimates of influenza activity in the US by leveraging data from multiple data sources including: Google searches, Twitter microblogs, nearly rea...
Natural Language Processing for Real-Time Catheter-Associated Urinary Tract Infection Surveillance: Results of a Pilot Implementation Trial.
Infection control and hospital epidemiology
May 29, 2015
BACKGROUND: Incidence of catheter-associated urinary tract infection (CAUTI) is a quality benchmark. To streamline conventional detection methods, an electronic surveillance system augmented with natural language processing (NLP), which gathers data ...
Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.
PloS one
May 4, 2015
For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data o...
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