Navigating the unseen peril: safeguarding medical imaging in the age of AI

In response to the increasing significance of artificial intelligence (AI) in healthcare, there has been increased attention – including a Presidential executive order to create an AI Safety Institute – to the potential threats posed by AI. While much attention has been given to the conventional ris...

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Main Authors: Alexandra Maertens, Steve Brykman, Thomas Hartung, Andrei Gafita, Harrison Bai, David Hoelzer, Ed Skoudis, Channing Judith Paller
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Artificial Intelligence
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Online Access:https://www.frontiersin.org/articles/10.3389/frai.2024.1400732/full
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author Alexandra Maertens
Steve Brykman
Thomas Hartung
Thomas Hartung
Andrei Gafita
Harrison Bai
David Hoelzer
Ed Skoudis
Channing Judith Paller
author_facet Alexandra Maertens
Steve Brykman
Thomas Hartung
Thomas Hartung
Andrei Gafita
Harrison Bai
David Hoelzer
Ed Skoudis
Channing Judith Paller
author_sort Alexandra Maertens
collection DOAJ
description In response to the increasing significance of artificial intelligence (AI) in healthcare, there has been increased attention – including a Presidential executive order to create an AI Safety Institute – to the potential threats posed by AI. While much attention has been given to the conventional risks AI poses to cybersecurity, and critical infrastructure, here we provide an overview of some unique challenges of AI for the medical community. Above and beyond obvious concerns about vetting algorithms that impact patient care, there are additional subtle yet equally important things to consider: the potential harm AI poses to its own integrity and the broader medical information ecosystem. Recognizing the role of healthcare professionals as both consumers and contributors to AI training data, this article advocates for a proactive approach in understanding and shaping the data that underpins AI systems, emphasizing the need for informed engagement to maximize the benefits of AI while mitigating the risks.
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spelling doaj-art-35d128d27e184a9f95947b25b5ca33c82024-12-09T16:13:30ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122024-12-01710.3389/frai.2024.14007321400732Navigating the unseen peril: safeguarding medical imaging in the age of AIAlexandra Maertens0Steve Brykman1Thomas Hartung2Thomas Hartung3Andrei Gafita4Harrison Bai5David Hoelzer6Ed Skoudis7Channing Judith Paller8Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United StatesIndependent Creative Technologist, Boston, MA, United StatesCenter for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United StatesCAAT Europe, University of Konstanz, Konstanz, GermanyRadiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesRadiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesSANS Technology Institute, Rockville, MD, United StatesSANS Technology Institute, Rockville, MD, United StatesDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesIn response to the increasing significance of artificial intelligence (AI) in healthcare, there has been increased attention – including a Presidential executive order to create an AI Safety Institute – to the potential threats posed by AI. While much attention has been given to the conventional risks AI poses to cybersecurity, and critical infrastructure, here we provide an overview of some unique challenges of AI for the medical community. Above and beyond obvious concerns about vetting algorithms that impact patient care, there are additional subtle yet equally important things to consider: the potential harm AI poses to its own integrity and the broader medical information ecosystem. Recognizing the role of healthcare professionals as both consumers and contributors to AI training data, this article advocates for a proactive approach in understanding and shaping the data that underpins AI systems, emphasizing the need for informed engagement to maximize the benefits of AI while mitigating the risks.https://www.frontiersin.org/articles/10.3389/frai.2024.1400732/fullmedical imagingartificial intelligencedata qualityprecision medicinedata bias
spellingShingle Alexandra Maertens
Steve Brykman
Thomas Hartung
Thomas Hartung
Andrei Gafita
Harrison Bai
David Hoelzer
Ed Skoudis
Channing Judith Paller
Navigating the unseen peril: safeguarding medical imaging in the age of AI
Frontiers in Artificial Intelligence
medical imaging
artificial intelligence
data quality
precision medicine
data bias
title Navigating the unseen peril: safeguarding medical imaging in the age of AI
title_full Navigating the unseen peril: safeguarding medical imaging in the age of AI
title_fullStr Navigating the unseen peril: safeguarding medical imaging in the age of AI
title_full_unstemmed Navigating the unseen peril: safeguarding medical imaging in the age of AI
title_short Navigating the unseen peril: safeguarding medical imaging in the age of AI
title_sort navigating the unseen peril safeguarding medical imaging in the age of ai
topic medical imaging
artificial intelligence
data quality
precision medicine
data bias
url https://www.frontiersin.org/articles/10.3389/frai.2024.1400732/full
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