Literature DB >> 34396058

Ethical Machine Learning in Healthcare.

Irene Y Chen1, Emma Pierson2, Sherri Rose3, Shalmali Joshi4, Kadija Ferryman5, Marzyeh Ghassemi1,6.   

Abstract

The use of machine learning (ML) in healthcare raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of healthcare. Specifically, we frame ethics of ML in healthcare through the lens of social justice. We describe ongoing efforts and outline challenges in a proposed pipeline of ethical ML in health, ranging from problem selection to postdeployment considerations. We close by summarizing recommendations to address these challenges.

Entities:  

Keywords:  bias; ethics; health; health disparities; healthcare; machine learning

Mesh:

Year:  2021        PMID: 34396058      PMCID: PMC8362902          DOI: 10.1146/annurev-biodatasci-092820-114757

Source DB:  PubMed          Journal:  Annu Rev Biomed Data Sci        ISSN: 2574-3414


  82 in total

1.  On error management: lessons from aviation.

Authors:  R L Helmreich
Journal:  BMJ       Date:  2000-03-18

2.  A critical evaluation of the morbidity and mortality conference.

Authors:  Kenric M Murayama; Anna M Derossis; Debra A DaRosa; Heather B Sherman; Jonathan P Fryer
Journal:  Am J Surg       Date:  2002-03       Impact factor: 2.565

3.  Global notes: the 10/90 gap disparities in global health research.

Authors:  D Vidyasagar
Journal:  J Perinatol       Date:  2006-01-01       Impact factor: 2.521

4.  Treating health disparities with artificial intelligence.

Authors:  Irene Y Chen; Shalmali Joshi; Marzyeh Ghassemi
Journal:  Nat Med       Date:  2020-01       Impact factor: 53.440

5.  Performance of racial and ethnic minority-serving hospitals on delivery-related indicators.

Authors:  Andreea A Creanga; Brian T Bateman; Jill M Mhyre; Elena Kuklina; Alexander Shilkrut; William M Callaghan
Journal:  Am J Obstet Gynecol       Date:  2014-06-05       Impact factor: 8.661

6.  Accuracy of race, ethnicity, and language preference in an electronic health record.

Authors:  Elissa V Klinger; Sara V Carlini; Irina Gonzalez; Stella St Hubert; Jeffrey A Linder; Nancy A Rigotti; Emily Z Kontos; Elyse R Park; Lucas X Marinacci; Jennifer S Haas
Journal:  J Gen Intern Med       Date:  2014-12-20       Impact factor: 5.128

7.  Overvaluing individual consent ignores risks to tribal participants.

Authors:  Krystal S Tsosie; Joseph M Yracheta; Donna Dickenson
Journal:  Nat Rev Genet       Date:  2019-07-15       Impact factor: 53.242

8.  Assessing the generalizability of randomized trial results to target populations.

Authors:  Elizabeth A Stuart; Catherine P Bradshaw; Philip J Leaf
Journal:  Prev Sci       Date:  2015-04

9.  Strategies for handling missing data in electronic health record derived data.

Authors:  Brian J Wells; Kevin M Chagin; Amy S Nowacki; Michael W Kattan
Journal:  EGEMS (Wash DC)       Date:  2013-12-17

10.  Feasibility of Using Real-World Data to Replicate Clinical Trial Evidence.

Authors:  Victoria L Bartlett; Sanket S Dhruva; Nilay D Shah; Patrick Ryan; Joseph S Ross
Journal:  JAMA Netw Open       Date:  2019-10-02
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  13 in total

Review 1.  DNA methylation-based predictors of health: applications and statistical considerations.

Authors:  Paul D Yousefi; Matthew Suderman; Ryan Langdon; Oliver Whitehurst; George Davey Smith; Caroline L Relton
Journal:  Nat Rev Genet       Date:  2022-03-18       Impact factor: 53.242

2.  Revisiting performance metrics for prediction with rare outcomes.

Authors:  Samrachana Adhikari; Sharon-Lise Normand; Jordan Bloom; David Shahian; Sherri Rose
Journal:  Stat Methods Med Res       Date:  2021-09-01       Impact factor: 2.494

Review 3.  Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches.

Authors:  Sara E Berger; Alexis T Baria
Journal:  Front Pain Res (Lausanne)       Date:  2022-06-02

4.  Machine learning and health need better values.

Authors:  Marzyeh Ghassemi; Shakir Mohamed
Journal:  NPJ Digit Med       Date:  2022-04-22

5.  An Optimized Hyperparameter of Convolutional Neural Network Algorithm for Bug Severity Prediction in Alzheimer's-Based IoT System.

Authors:  Iqra Yousaf; Fareeha Anwar; Salma Imtiaz; Ahmad S Almadhor; Farruh Ishmanov; Sung Won Kim
Journal:  Comput Intell Neurosci       Date:  2022-06-28

6.  A joint fairness model with applications to risk predictions for underrepresented populations.

Authors:  Hyungrok Do; Shinjini Nandi; Preston Putzel; Padhraic Smyth; Judy Zhong
Journal:  Biometrics       Date:  2022-02-10       Impact factor: 1.701

7.  Improving the Performance of Risk Adjustment Systems: Constrained Regressions, Reinsurance, and Variable Selection.

Authors:  Thomas G McGuire; Anna L Zink; Sherri Rose
Journal:  Am J Health Econ       Date:  2021-10-04

8.  Identifying undercompensated groups defined by multiple attributes in risk adjustment.

Authors:  Anna Zink; Sherri Rose
Journal:  BMJ Health Care Inform       Date:  2021-09

9.  A comparison of approaches to improve worst-case predictive model performance over patient subpopulations.

Authors:  Stephen R Pfohl; Haoran Zhang; Yizhe Xu; Agata Foryciarz; Marzyeh Ghassemi; Nigam H Shah
Journal:  Sci Rep       Date:  2022-02-28       Impact factor: 4.379

Review 10.  Implementation of prognostic machine learning algorithms in paediatric chronic respiratory conditions: a scoping review.

Authors:  Nicole Filipow; Eleanor Main; Neil J Sebire; John Booth; Andrew M Taylor; Gwyneth Davies; Sanja Stanojevic
Journal:  BMJ Open Respir Res       Date:  2022-03
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