Literature DB >> 33250145

The automation of bias in medical Artificial Intelligence (AI): Decoding the past to create a better future.

Isabel Straw1.   

Abstract

Medicine is at a disciplinary crossroads. With the rapid integration of Artificial Intelligence (AI) into the healthcare field the future care of our patients will depend on the decisions we make now. Demographic healthcare inequalities continue to persist worldwide and the impact of medical biases on different patient groups is still being uncovered by the research community. At a time when clinical AI systems are scaled up in response to the Covid19 pandemic, the role of AI in exacerbating health disparities must be critically reviewed. For AI to account for the past and build a better future, we must first unpack the present and create a new baseline on which to develop these tools. The means by which we move forwards will determine whether we project existing inequity into the future, or whether we reflect on what we hold to be true and challenge ourselves to be better. AI is an opportunity and a mirror for all disciplines to improve their impact on society and for medicine the stakes could not be higher. Crown
Copyright © 2020. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Bias; Data science; Digital health; Disparities; Health; Healthcare; Inequality; Medicine

Year:  2020        PMID: 33250145     DOI: 10.1016/j.artmed.2020.101965

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  5 in total

1.  Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

Authors:  Ayis Pyrros; Jorge Mario Rodríguez-Fernández; Stephen M Borstelmann; Judy Wawira Gichoya; Jeanne M Horowitz; Brian Fornelli; Nasir Siddiqui; Yury Velichko; Oluwasanmi Koyejo Sanmi; William Galanter
Journal:  J Am Coll Radiol       Date:  2022-01       Impact factor: 5.532

2.  An artificial intelligence-based risk prediction model of myocardial infarction.

Authors:  Ran Liu; Miye Wang; Tao Zheng; Rui Zhang; Nan Li; Zhongxiu Chen; Hongmei Yan; Qingke Shi
Journal:  BMC Bioinformatics       Date:  2022-06-07       Impact factor: 3.307

Review 3.  Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.

Authors:  Isabel Straw; Honghan Wu
Journal:  BMJ Health Care Inform       Date:  2022-04

4.  Bibliometric analysis of research themes and trends in childhood autism spectrum disorders from 2012 to 2021.

Authors:  Junqiang Zhao; Yi Lu; Xingyang Wu; Fujun Zhou; Fangqin Fei; Xiaoyan Wu; Xiufang Ding; Minli Wang
Journal:  Front Public Health       Date:  2022-08-31

5.  Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19-Positive Critical Care Patients.

Authors:  Jenny Alderden; Susan M Kennerly; Andrew Wilson; Jonathan Dimas; Casey McFarland; David Y Yap; Lucy Zhao; Tracey L Yap
Journal:  Comput Inform Nurs       Date:  2022-10-01       Impact factor: 2.146

  5 in total

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