Commercialization of medical artificial intelligence technologies: challenges and opportunities

Artificial intelligence (AI) is already having a significant impact on healthcare. For example, AI-guided imaging can improve the diagnosis/treatment of vascular diseases, which affect over 200 million people globally. Recently, Chiu and colleagues (2024) developed an AI algorithm that supports nurs...

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Main Authors: Ben Li, Dylan Powell, Regent Lee
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01867-w
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author Ben Li
Dylan Powell
Regent Lee
author_facet Ben Li
Dylan Powell
Regent Lee
author_sort Ben Li
collection DOAJ
description Artificial intelligence (AI) is already having a significant impact on healthcare. For example, AI-guided imaging can improve the diagnosis/treatment of vascular diseases, which affect over 200 million people globally. Recently, Chiu and colleagues (2024) developed an AI algorithm that supports nurses with no ultrasound training in diagnosing abdominal aortic aneurysms (AAA) with similar accuracy as ultrasound-trained physicians. This technology can therefore improve AAA screening; however, achieving clinical impact with new AI technologies requires careful consideration of commercialization strategies, including funding, compliance with safety and regulatory frameworks, health technology assessment, regulatory approval, reimbursement, and clinical guideline integration.
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spelling doaj-art-c7ca16c19ad843faabf07bc8cb5a3cf72025-08-20T03:06:08ZengNature Portfolionpj Digital Medicine2398-63522025-07-01811410.1038/s41746-025-01867-wCommercialization of medical artificial intelligence technologies: challenges and opportunitiesBen Li0Dylan Powell1Regent Lee2Division of Vascular Surgery, University of TorontoFaculty of Health Sciences & Sport, University of StirlingNuffield Department of Surgical Sciences, University of OxfordArtificial intelligence (AI) is already having a significant impact on healthcare. For example, AI-guided imaging can improve the diagnosis/treatment of vascular diseases, which affect over 200 million people globally. Recently, Chiu and colleagues (2024) developed an AI algorithm that supports nurses with no ultrasound training in diagnosing abdominal aortic aneurysms (AAA) with similar accuracy as ultrasound-trained physicians. This technology can therefore improve AAA screening; however, achieving clinical impact with new AI technologies requires careful consideration of commercialization strategies, including funding, compliance with safety and regulatory frameworks, health technology assessment, regulatory approval, reimbursement, and clinical guideline integration.https://doi.org/10.1038/s41746-025-01867-w
spellingShingle Ben Li
Dylan Powell
Regent Lee
Commercialization of medical artificial intelligence technologies: challenges and opportunities
npj Digital Medicine
title Commercialization of medical artificial intelligence technologies: challenges and opportunities
title_full Commercialization of medical artificial intelligence technologies: challenges and opportunities
title_fullStr Commercialization of medical artificial intelligence technologies: challenges and opportunities
title_full_unstemmed Commercialization of medical artificial intelligence technologies: challenges and opportunities
title_short Commercialization of medical artificial intelligence technologies: challenges and opportunities
title_sort commercialization of medical artificial intelligence technologies challenges and opportunities
url https://doi.org/10.1038/s41746-025-01867-w
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AT dylanpowell commercializationofmedicalartificialintelligencetechnologieschallengesandopportunities
AT regentlee commercializationofmedicalartificialintelligencetechnologieschallengesandopportunities