Literature DB >> 31234654

Healthcare uses of artificial intelligence: Challenges and opportunities for growth.

Eric Racine1,2,3,4, Wren Boehlen1, Matthew Sample1,2.   

Abstract

Forms of Artificial Intelligence (AI), like deep learning algorithms and neural networks, are being intensely explored for novel healthcare applications in areas such as imaging and diagnoses, risk analysis, lifestyle management and monitoring, health information management, and virtual health assistance. Expected benefits in these areas are wide-ranging and include increased speed in imaging, greater insight into predictive screening, and decreased healthcare costs and inefficiency. However, AI-based clinical tools also create a host of situations wherein commonly-held values and ethical principles may be challenged. In this short column, we highlight three potentially problematic aspects of AI use in healthcare: (1) dynamic information and consent, (2) transparency and ownership, and (3) privacy and discrimination. We discuss their impact on patient/client, clinician, and health institution values and suggest ways to tackle this impact. We propose that AI-related ethical challenges may represent an opportunity for growth in organizations.

Entities:  

Year:  2019        PMID: 31234654     DOI: 10.1177/0840470419843831

Source DB:  PubMed          Journal:  Healthc Manage Forum        ISSN: 0840-4704


  8 in total

1.  Identifying Ethical Considerations for Machine Learning Healthcare Applications.

Authors:  Danton S Char; Michael D Abràmoff; Chris Feudtner
Journal:  Am J Bioeth       Date:  2020-11       Impact factor: 11.229

2.  Machine vs. Radiologist-Based Translations of RadLex: Implications for Multi-language Report Interoperability.

Authors:  Christian J Park; Paul H Yi; Hussain Al Yousif; Kenneth C Wang
Journal:  J Digit Imaging       Date:  2022-02-15       Impact factor: 4.903

3.  The use of personal health information outside the circle of care: consent preferences of patients from an academic health care institution.

Authors:  Sarah Tosoni; Indu Voruganti; Katherine Lajkosz; Flavio Habal; Patricia Murphy; Rebecca K S Wong; Donald Willison; Carl Virtanen; Ann Heesters; Fei-Fei Liu
Journal:  BMC Med Ethics       Date:  2021-03-24       Impact factor: 2.652

Review 4.  What Makes Artificial Intelligence Exceptional in Health Technology Assessment?

Authors:  Jean-Christophe Bélisle-Pipon; Vincent Couture; Marie-Christine Roy; Isabelle Ganache; Mireille Goetghebeur; I Glenn Cohen
Journal:  Front Artif Intell       Date:  2021-11-02

Review 5.  Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea.

Authors:  Hannah L Brennan; Simon D Kirby
Journal:  J Otolaryngol Head Neck Surg       Date:  2022-04-25

6.  The ethical, legal and social implications of using artificial intelligence systems in breast cancer care.

Authors:  Stacy M Carter; Wendy Rogers; Khin Than Win; Helen Frazer; Bernadette Richards; Nehmat Houssami
Journal:  Breast       Date:  2019-10-11       Impact factor: 4.380

7.  Translational health technology and system schemes: enhancing the dynamics of health informatics.

Authors:  Marjo Rissanen
Journal:  Health Inf Sci Syst       Date:  2020-11-09

8.  Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.

Authors:  Jerry M Spiegel; Rodney Ehrlich; Annalee Yassi; Francisco Riera; James Wilkinson; Karen Lockhart; Stephen Barker; Barry Kistnasamy
Journal:  Ann Glob Health       Date:  2021-07-01       Impact factor: 2.462

  8 in total

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