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Clinical Specialty Expansion of AI-Enabled and Machine Learning–Enabled Medical Devices Authorized by the US Food and Drug Administration From 1995 to 2025: Longitudinal Content Analysis

Youn-Soo Lee, Bo-Young Youn

Journal of Medical Internet Research · 2026

Vollständiger Abstract

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Abstract Background The US Food and Drug Administration (FDA) has authorized AI-enabled and machine learning (ML)–enabled medical devices since 1995 and maintains a public registry of these authorizations. Prior analyses report that radiology dominates this landscape, but whether that concentration has persisted, intensified, or begun to reverse across 3 decades, particularly since 2022, remains insufficiently characterized. Objective This study aimed to (1) characterize the longitudinal growth of FDA-authorized AI/ML-enabled devices from 1995 to 2025, (2) quantify the temporal evolution of clinical specialty distribution across 4 eras, (3) identify emerging specialties, and (4) examine the association between manufacturer type and nonradiology authorization. Methods All 1430 devices in the FDA AI-Enabled Medical Devices registry (downloaded on March 1, 2026) with final marketing-authorization decisions through December 31, 2025, were analyzed. Devices were stratified by clinical specialty (FDA advisory committee panel) and 4 eras: Era 1 (1995‐2015), Era 2 (2016‐2019), Era 3 (2020‐2022), and Era 4 (2023‐2025). Concentration was quantified using the Herfindahl-Hirschman Index (HHI) with bootstrap CIs; the Cochran-Armitage test assessed trends in specialty share, with Bonferroni correction. Multivariable logistic regression estimated the odds of nonradiology authorization by manufacturer type and era, with an era-by-manufacturer interaction term. Sensitivity analyses used cluster-robust standard errors, a continuous authorization year variable, and Firth penalized regression. Manufacturers were classified using FDA records, Crunchbase, PitchBook, and company websites. Results Annual authorizations rose from a mean of 2.0 (SD 2.0) in Era 1 to a mean of 264 (SD 58.2) in Era 4, with 331 authorizations in 2025 alone; the 510(k) pathway accounted for 96.2% (1376/1430). Radiology led in every era but followed a nonmonotonic trajectory, rising from 35.7% (15/42, Era 1) to a peak of 85.5% (347/406, Era 3) before declining to 77.5% (614/792, Era 4), the first significant decline on record ( P =.001). The HHI fell from 0.738 (Era 3) to 0.612 (Era 4; bootstrap P

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Publikationsdaten

Autor:innen
Youn-Soo Lee, Bo-Young Youn
Quelle
Journal of Medical Internet Research
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
1438-8871
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Zitierfähiger Nachweis

Youn-Soo Lee, Bo-Young Youn (2026). Clinical Specialty Expansion of AI-Enabled and Machine Learning–Enabled Medical Devices Authorized by the US Food and Drug Administration From 1995 to 2025: Longitudinal Content Analysis. Journal of Medical Internet Research. https://doi.org/10.2196/103040
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