AIMC Topic: Epidemiologic Methods

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Machine learning in causal inference for epidemiology.

European journal of epidemiology Nov 13, 2024
In causal inference, parametric models are usually employed to address causal questions estimating the effect of interest. However, parametric models rely on the correct model specification assumption that, if not met, leads to biased effect estimate...
Models, Statistical Likelihood Functions Epidemiologic Methods Epidemiology Humans Machine Learning Causality
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Don't Let Your Analysis Go to Seed: On the Impact of Random Seed on Machine Learning-based Causal Inference.

Epidemiology (Cambridge, Mass.) Aug 16, 2024
Machine learning techniques for causal effect estimation can enhance the reliability of epidemiologic analyses, reducing their dependence on correct model specifications. However, the stochastic nature of many machine learning algorithms implies that...
Reproducibility of Results Causality Models, Statistical Epidemiologic Methods Machine Learning Algorithms Computer Simulation Humans
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Predictive value of a novel Asian lung cancer screening nomogram based on artificial intelligence and epidemiological characteristics.

Thoracic cancer Oct 28, 2021
BACKGROUND: To develop and validate a risk prediction nomogram based on a deep learning convolutional neural networks (CNN) model and epidemiological characteristics for lung cancer screening in patients with small pulmonary nodules (SPN).
Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies China Lung Neoplasms Epidemiologic Methods Early Detection of Cancer Aged Tomography, X-Ray Computed Nomograms Predictive Value of Tests Male Female Middle Aged Risk Factors
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Dynamical footprints enable detection of disease emergence.

PLoS biology May 20, 2020
Developing methods for anticipating the emergence or reemergence of infectious diseases is both important and timely; however, traditional model-based approaches are stymied by uncertainty surrounding the underlying drivers. Here, we demonstrate an o...
Humans Supervised Machine Learning Epidemiologic Methods Communicable Diseases, Emerging Vaccine-Preventable Diseases Vector Borne Diseases
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Machine Learning in Epidemiology and Health Outcomes Research.

Annual review of public health Oct 2, 2019
Machine learning approaches to modeling of epidemiologic data are becoming increasingly more prevalent in the literature. These methods have the potential to improve our understanding of health and opportunities for intervention, far beyond our past ...
Epidemiologic Research Design Machine Learning Outcome Assessment, Health Care Epidemiologic Methods Humans
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Applications of machine learning techniques to predict filariasis using socio-economic factors.

Epidemiology and infection Sep 2, 2019
Filariasis is one of the major public health concerns in India. Approximately 600 million people spread across 250 districts of India are at risk of filariasis. To predict this disease, a pilot scale study was carried out in 30 villages of Karimnagar...
ROC Curve India Socioeconomic Factors Filariasis Models, Statistical Epidemiologic Methods Humans Machine Learning
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An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

Nutrients Jun 8, 2019
BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research out...
Epidemiologic Methods Biological Ontologies Terminology as Topic Nutritional Sciences Humans Data Analysis Data Accuracy Information Dissemination Biomedical Research Diet
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Assessing patient risk of central line-associated bacteremia via machine learning.

American journal of infection control Apr 13, 2018
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLAB...
Young Adult Adult Male Infant Case-Control Studies Middle Aged Risk Assessment Infant, Newborn Aged Aged, 80 and over Machine Learning Retrospective Studies Female Humans Epidemiologic Methods Bacteremia Catheterization, Central Venous Catheter-Related Infections Adolescent Academic Medical Centers Child, Preschool Child
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Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Epidemiology and infection Jan 24, 2017
Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for the prevention and control of TB. This study proposes a hybrid model combining autoregressive integrat...
Neural Networks, Computer Forecasting China Humans Tuberculosis Epidemiologic Methods Incidence Communicable Disease Control Time Factors Models, Statistical
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Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

Occupational and environmental medicine Apr 21, 2016
BACKGROUND: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we de...
Occupations United States Occupational Safety and Health Administration United States Reproducibility of Results Natural Language Processing Job Description Humans Case-Control Studies Epidemiologic Studies Epidemiologic Methods Software Logistic Models Industry Algorithms Carcinoma, Renal Cell
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