AIMC Topic: Epidemiological Monitoring

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Comparing machine learning with case-control models to identify confirmed dengue cases.

PLoS neglected tropical diseases Nov 10, 2020
In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have appli...
Adult Male Middle Aged Public Health Female Aged Young Adult Models, Statistical Developing Countries Epidemiological Monitoring Dengue Disease Outbreaks Case-Control Studies Humans Adolescent Machine Learning
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Forecasting tuberculosis using diabetes-related google trends data.

Pathogens and global health May 26, 2020
Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit the converging nature of the tuberculosis (TB) and diabetes epidemics to forecast TB case numbers. Thus, we extended TB prediction models based on tr...
Diabetes Mellitus Tuberculosis Germany Epidemics Epidemiological Monitoring Humans Neural Networks, Computer Machine Learning Forecasting
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Ethics and governance for digital disease surveillance.

Science (New York, N.Y.) May 11, 2020
Humans COVID-19 Forecasting Confidentiality Coronavirus Infections Artificial Intelligence Machine Learning Pandemics Datasets as Topic Epidemiological Monitoring Pneumonia, Viral
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Prediction of the Vaccine-derived Poliovirus Outbreak Incidence: A Hybrid Machine Learning Approach.

Scientific reports Mar 19, 2020
Recently, significant attention has been devoted to vaccine-derived poliovirus (VDPV) surveillance due to its severe consequences. Prediction of the outbreak incidence of VDPF requires an accurate analysis of the alarming data. The overarching aim to...
Poliomyelitis Poliovirus Poliovirus Vaccines Epidemiological Monitoring Paraplegia Laos Humans Machine Learning Algorithms Forecasting Disease Outbreaks Incidence
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Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study.

Journal of medical Internet research Nov 4, 2019
BACKGROUND: Tools used to appraise the credibility of health information are time-consuming to apply and require context-specific expertise, limiting their use for quickly identifying and mitigating the spread of misinformation as it emerges.
Social Networking Retrospective Studies Social Media Vaccines Epidemiological Monitoring Humans Machine Learning
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A comparison of machine learning algorithms for the surveillance of autism spectrum disorder.

PloS one Sep 25, 2019
OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speedi...
Child United States Support Vector Machine Humans Public Health Surveillance Centers for Disease Control and Prevention, U.S. Autism Spectrum Disorder Feasibility Studies Prevalence Epidemiological Monitoring Deep Learning Georgia
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Artificial Intelligence Methods for Surgical Site Infection: Impacts on Detection, Monitoring, and Decision Making.

Surgical infections Aug 27, 2019
There has been tremendous growth in the amount of new surgical site infection (SSI) data generated. Key challenges exist in understanding the data for robust clinical decision-support. Limitations of traditional methodologies to handle these data le...
Epidemiological Monitoring Humans Artificial Intelligence Image Processing, Computer-Assisted Decision Making Surgical Wound Infection Disease Management
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Automatic classification of free-text medical causes from death certificates for reactive mortality surveillance in France.

International journal of medical informatics Jul 6, 2019
BACKGROUND: Mortality surveillance is of fundamental importance to public health surveillance. The real-time recording of death certificates, thanks to Electronic Death Registration System (EDRS), provides valuable data for reactive mortality surveil...
Humans Adult Male Support Vector Machine Public Health Surveillance Death Certificates France Classification Cause of Death Disease Supervised Machine Learning Epidemiological Monitoring
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Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China.

Scientific reports May 29, 2019
The high incidence, seasonal pattern and frequent outbreaks of hand, foot, and mouth disease (HFMD) represent a threat for millions of children in mainland China. And advanced response is being used to address this. Here, we aimed to model time serie...
Humans Epidemics Epidemiological Monitoring Forecasting Hand, Foot and Mouth Disease Computer Simulation Child, Preschool Models, Statistical Deep Learning Seasons China Datasets as Topic Incidence
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In vitro activity of eravacycline against 2213 Gram-negative and 2424 Gram-positive bacterial pathogens isolated in Canadian hospital laboratories: CANWARD surveillance study 2014-2015.

Diagnostic microbiology and infectious disease Dec 22, 2017
Gram-negative (n=2213) and Gram-positive (n=2424) pathogens isolated from patients in 13 Canadian hospitals in 2014 and 2015 were tested for in vitro susceptibility to eravacycline and comparators using the Clinical and Laboratory Standards Institute...
Gram-Positive Bacterial Infections Enterobacteriaceae Infections Epidemiological Monitoring Humans Gram-Negative Bacterial Infections Anti-Bacterial Agents Canada Laboratories, Hospital Microbial Sensitivity Tests Enterobacteriaceae Tetracyclines Gram-Negative Bacteria Gram-Positive Bacteria
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