AIMC Topic: Population Surveillance

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A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.

Zoonoses and public health Jul 15, 2019
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...
Humans Animals Population Surveillance Iran Data Mining Zoonoses Brucellosis Support Vector Machine Models, Statistical
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Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR Jun 20, 2019
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...
Disease Susceptibility Genetic Predisposition to Disease Models, Theoretical Population Surveillance Female Adult Breast Neoplasms Big Data ROC Curve Middle Aged Risk Assessment Algorithms Precision Medicine Prognosis Humans Machine Learning
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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants.

PloS one May 15, 2019
BACKGROUND: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-op...
Reproducibility of Results United Kingdom Risk Factors Prospective Studies Proportional Hazards Models Male Prognosis Female Population Surveillance Biological Specimen Banks Humans Cardiovascular Diseases Machine Learning Risk Assessment Algorithms
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Artificial intelligence: opportunities and risks for public health.

The Lancet. Digital health May 2, 2019
Machine Learning Precision Medicine Public Health Population Surveillance Humans Artificial Intelligence Preventive Health Services
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Chief complaint classification with recurrent neural networks.

Journal of biomedical informatics Mar 26, 2019
Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automated classification of these records can improve outbreak detection speed and diagnosis accuracy. Curre...
Neural Networks, Computer Algorithms Population Surveillance Humans Triage
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Drivers for the development of an Animal Health Surveillance Ontology (AHSO).

Preventive veterinary medicine Mar 9, 2019
Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields ...
Biological Ontologies Sentinel Surveillance Animals Population Surveillance
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Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations.

Journal of medical Internet research Feb 20, 2019
BACKGROUND: The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, social media-based data obtained directly from people are particularly valuable and are attracting signif...
Social Media Natural Language Processing Internet Data Mining Machine Learning Databases, Factual Population Surveillance Humans
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Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Clinical & experimental ophthalmology Jul 4, 2018
IMPORTANCE: Diagnosis codes are inadequate for accurately identifying herpes zoster (HZ) ophthalmicus (HZO). There is significant lack of population-based studies on HZO due to the high expense of manual review of medical records.
ROC Curve Follow-Up Studies Population Surveillance Retrospective Studies Humans Female Eye Infections, Viral Reproducibility of Results Algorithms Herpes Zoster Ophthalmicus Aged Natural Language Processing Aged, 80 and over Male Herpesvirus 3, Human Young Adult Middle Aged Adult Adolescent
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Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
The United States is in the midst of a prescription opioid epidemic, with the number of yearly opioid-related overdose deaths increasing almost fourfold since 2000. To more effectively prevent unintentional opioid overdoses, the medical profession re...
Opioid-Related Disorders Population Surveillance Humans Datasets as Topic Electronic Health Records Natural Language Processing False Positive Reactions Support Vector Machine Analgesics, Opioid
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Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PloS one Apr 2, 2018
Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in ...
Models, Statistical Population Surveillance Humans Seasons Forecasting Neural Networks, Computer Dengue Reproducibility of Results Algorithms Brazil
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