AIMC Topic: Selection Bias

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Using machine learning to identify structural breaks in single-group interrupted time series designs.

Journal of evaluation in clinical practice Apr 19, 2016
RATIONALE, AIMS AND OBJECTIVES: Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the interve...
Interrupted Time Series Analysis Male Middle Aged Discriminant Analysis Selection Bias Female Adult Research Design Humans Machine Learning
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The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

Medical decision making : an international journal of the Society for Medical Decision Making Dec 1, 2014
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort ...
Male Middle Aged Diabetes Mellitus, Type 2 Models, Theoretical Iran Humans Bayes Theorem Adult Minority Groups Sensitivity and Specificity Prospective Studies Selection Bias Risk Factors Socioeconomic Factors Neural Networks, Computer Female Decision Trees Algorithms
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Citations alone were enough to predict favorable conclusions in reviews of neuraminidase inhibitors.

Journal of clinical epidemiology Oct 22, 2014
OBJECTIVES: To examine the use of supervised machine learning to identify biases in evidence selection and determine if citation information can predict favorable conclusions in reviews about neuraminidase inhibitors.
Review Literature as Topic Enzyme Inhibitors Publications Neuraminidase Artificial Intelligence Influenza, Human Humans Research Design Selection Bias
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The effect of selection bias on the performance of a deep learning-based intraoperative hypotension prediction model using real-world samples from a publicly available database.

British journal of anaesthesia Sep 1, 2025
BACKGROUND: There are models to predict intraoperative hypotension from arterial pressure waveforms. Selection bias in datasets used for model development and validation could impact model performance. We aimed to evaluate how selection bias affects ...
Predictive Value of Tests Hypotension Deep Learning Monitoring, Intraoperative Arterial Pressure Female Intraoperative Complications Aged Selection Bias Humans Databases, Factual Male Datasets as Topic Prospective Studies Middle Aged
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The Impact of Undersampling on the Predictive Performance of Logistic Regression and Machine Learning Algorithms: A Simulation Study.

Epidemiology (Cambridge, Mass.) Sep 1, 2020
Humans Machine Learning Logistic Models Selection Bias Algorithms Computer Simulation
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