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Bias

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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
OBJECTIVES: To highlight the often overlooked role of user interface (UI) design in mitigating bias in artificial intelligence (AI)-based clinical decision support (CDS).

Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging.

Journal of the American Medical Informatics Association : JAMIA
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...

How Data Infrastructure Deals with Bias Problems in Medical Imaging.

Studies in health technology and informatics
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...

Overcoming "Fear of AI" Bias: Insights from the Technology Acceptance Model.

Radiographics : a review publication of the Radiological Society of North America, Inc

Machine Learning in Health Care: Ethical Considerations Tied to Privacy, Interpretability, and Bias.

North Carolina medical journal
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...

Understanding and Mitigating Bias in Imaging Artificial Intelligence.

Radiographics : a review publication of the Radiological Society of North America, Inc
Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. m...

Unmasking bias in artificial intelligence: a systematic review of bias detection and mitigation strategies in electronic health record-based models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Leveraging artificial intelligence (AI) in conjunction with electronic health records (EHRs) holds transformative potential to improve healthcare. However, addressing bias in AI, which risks worsening healthcare disparities, cannot be ove...