AIMC Topic: Bias

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How Effective Are Machine Learning and Doubly Robust Estimators in Incorporating High-Dimensional Proxies to Reduce Residual Confounding?

Pharmacoepidemiology and drug safety May 1, 2025
BACKGROUND: Residual confounding presents a persistent challenge in observational studies, particularly in high-dimensional settings. High-dimensional proxy adjustment methods, such as the high-dimensional propensity score (hdPS), are widely used to ...
Computer Simulation Logistic Models Humans Machine Learning Propensity Score Likelihood Functions Confounding Factors, Epidemiologic Observational Studies as Topic Bias
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Generative Artificial Intelligence Biases, Limitations and Risks in Nuclear Medicine: An Argument for Appropriate Use Framework and Recommendations.

Seminars in nuclear medicine May 1, 2025
Generative artificial intelligence (AI) algorithms for both text-to-text and text-to-image applications have seen rapid and widespread adoption in the general and medical communities. While limitations of generative AI have been widely reported, ther...
Risk Nuclear Medicine Generative Artificial Intelligence Bias Humans Artificial Intelligence
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Using human factors methods to mitigate bias in artificial intelligence-based clinical decision support.

Journal of the American Medical Informatics Association : JAMIA Feb 1, 2025
OBJECTIVES: To highlight the often overlooked role of user interface (UI) design in mitigating bias in artificial intelligence (AI)-based clinical decision support (CDS).
Machine Learning Algorithms Humans Artificial Intelligence Bias Ergonomics User-Computer Interface Decision Support Systems, Clinical
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Is there a competitive advantage to using multivariate statistical or machine learning methods over the Bross formula in the hdPS framework for bias and variance estimation?

PloS one Jan 1, 2025
PURPOSE: We aim to evaluate various proxy selection methods within the context of high-dimensional propensity score (hdPS) analysis. This study aimed to systematically evaluate and compare the performance of traditional statistical methods and machin...
Humans Models, Statistical Bias Multivariate Analysis Propensity Score Computer Simulation Nutrition Surveys Machine Learning Algorithms
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Automatic large-scale political bias detection of news outlets.

PloS one Jan 1, 2025
Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when interacting with online news is of crucial import. However, quantifying political bias is problematic. To ...
Politics Mass Media Bias Humans Internet Machine Learning
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Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2024
OBJECTIVE: Artificial intelligence (AI) models trained using medical images for clinical tasks often exhibit bias in the form of subgroup performance disparities. However, since not all sources of bias in real-world medical imaging data are easily id...
Artificial Intelligence Diagnostic Imaging Bias Neuroimaging Humans Neural Networks, Computer
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How Data Infrastructure Deals with Bias Problems in Medical Imaging.

Studies in health technology and informatics Aug 22, 2024
The paper discusses biases in medical imaging analysis, particularly focusing on the challenges posed by the development of machine learning algorithms and generative models. It introduces a taxonomy of bias problems and addresses them through a data...
Bias Confidentiality Humans Computer Security Machine Learning Algorithms Diagnostic Imaging
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Overcoming "Fear of AI" Bias: Insights from the Technology Acceptance Model.

Radiographics : a review publication of the Radiological Society of North America, Inc Aug 1, 2024
Bias Fear Humans Artificial Intelligence
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Machine Learning in Health Care: Ethical Considerations Tied to Privacy, Interpretability, and Bias.

North Carolina medical journal Jun 1, 2024
Machine learning models hold great promise with medical applications, but also give rise to a series of ethical challenges. In this survey we focus on training data, model interpretability and bias and the related issues tied to privacy, autonomy, an...
Confidentiality Privacy Delivery of Health Care Humans Bias Machine Learning
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Using AI to improve medication safety.

Nature medicine Jun 1, 2024
Language Bias Medication Errors Artificial Intelligence Prescription Drugs Health Personnel
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