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Implementing an AI algorithm in the clinical setting: a case study for the accuracy paradox.
Eur Radiol
December 2024
Department of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Objectives: We report our experience implementing an algorithm for the detection of large vessel occlusion (LVO) for suspected stroke in the emergency setting, including its performance, and offer an explanation as to why it was poorly received by radiologists.
Materials And Methods: An algorithm was deployed in the emergency room at a single tertiary care hospital for the detection of LVO on CT angiography (CTA) between September 1st-27th, 2021. A retrospective analysis of the algorithm's accuracy was performed.
Fantasies and Fallacies of 'Aesthetic' Instagrammers.
Indian J Plast Surg
December 2024
Aesthetique, Plastic and Cosmetic Surgery Centre, Gujarat, India.
The influence of Instagram, as a social media platform, in shaping perceptions of aesthetic surgery cannot be understated. The idea of a more "aesthetic" self cultivates a desire for cosmetic enhancements. This article underscores the profound impact of Instagram on aesthetic surgery, shedding light on both its fantasies and fallacies.
View Article and Find Full Text PDFChallenging the "norm": a critical look at deaf-hearing comparison studies in research.
J Deaf Stud Deaf Educ
December 2024
Georgia State University P.O. Box 3965 Atlanta, GA 30302-3965, United States.
This study critically examines the biases and methodological shortcomings in studies comparing deaf and hearing populations, demonstrating their implications for both the reliability and ethics of research in deaf education. Upon reviewing the 20 most-cited deaf-hearing comparison studies, we identified recurring fallacies such as the presumption of hearing ideological biases, the use of heterogeneously small samples, and the misinterpretation of critical variables. Our research reveals a propensity to biased conclusions based on the norms of white, hearing, monolingual English speakers.
View Article and Find Full Text PDFWhen time is of the essence: ethical reconsideration of XAI in time-sensitive environments.
J Med Ethics
September 2024
National Center for Tumor Diseases (NCT) Heidelberg, NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Germany, Heidelberg University, Medical Faculty Heidelberg, Heidelberg University Hospital, Department of Medical Oncology, Section Translational Medical Ethics, Heidelberg, Germany.
The objective of explainable artificial intelligence systems designed for clinical decision support (XAI-CDSS) is to enhance physicians' diagnostic performance, confidence and trust through the implementation of interpretable methods, thus providing for a superior epistemic positioning, a robust foundation for critical reflection and trustworthiness in times of heightened technological dependence. However, recent studies have revealed shortcomings in achieving these goals, questioning the widespread endorsement of XAI by medical professionals, ethicists and policy-makers alike. Based on a surgical use case, this article challenges generalising calls for XAI-CDSS and emphasises the significance of time-sensitive clinical environments which frequently preclude adequate consideration of system explanations.
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