How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations

Abstract We reviewed 1016 FDA authorizations of AI/ML-enabled medical devices to develop a taxonomy capturing key variations in clinical and AI-related features. Quantitative image analysis remains the most common application, but its relative proportion has declined recently. Over 100 devices lever...

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Main Authors: Rohan Singh, Monika Bapna, Abdul Rahman Diab, Emily S. Ruiz, William Lotter
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01800-1
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author Rohan Singh
Monika Bapna
Abdul Rahman Diab
Emily S. Ruiz
William Lotter
author_facet Rohan Singh
Monika Bapna
Abdul Rahman Diab
Emily S. Ruiz
William Lotter
author_sort Rohan Singh
collection DOAJ
description Abstract We reviewed 1016 FDA authorizations of AI/ML-enabled medical devices to develop a taxonomy capturing key variations in clinical and AI-related features. Quantitative image analysis remains the most common application, but its relative proportion has declined recently. Over 100 devices leverage AI for data generation, though none yet involve LLMs. Our taxonomy clarifies current AI usage in medical devices and provides a foundation for tracking developments as applications evolve.
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institution Kabale University
issn 2398-6352
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publishDate 2025-07-01
publisher Nature Portfolio
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series npj Digital Medicine
spelling doaj-art-4b9f9db658d64c9582d07d1c18eb05932025-08-20T03:42:00ZengNature Portfolionpj Digital Medicine2398-63522025-07-01811610.1038/s41746-025-01800-1How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizationsRohan Singh0Monika Bapna1Abdul Rahman Diab2Emily S. Ruiz3William Lotter4Dana-Farber Cancer InstituteBrigham & Women’s HospitalDana-Farber Cancer InstituteBrigham & Women’s HospitalDana-Farber Cancer InstituteAbstract We reviewed 1016 FDA authorizations of AI/ML-enabled medical devices to develop a taxonomy capturing key variations in clinical and AI-related features. Quantitative image analysis remains the most common application, but its relative proportion has declined recently. Over 100 devices leverage AI for data generation, though none yet involve LLMs. Our taxonomy clarifies current AI usage in medical devices and provides a foundation for tracking developments as applications evolve.https://doi.org/10.1038/s41746-025-01800-1
spellingShingle Rohan Singh
Monika Bapna
Abdul Rahman Diab
Emily S. Ruiz
William Lotter
How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
npj Digital Medicine
title How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
title_full How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
title_fullStr How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
title_full_unstemmed How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
title_short How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations
title_sort how ai is used in fda authorized medical devices a taxonomy across 1 016 authorizations
url https://doi.org/10.1038/s41746-025-01800-1
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