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. 2020 Sep 11:3:118.
doi: 10.1038/s41746-020-00324-0. eCollection 2020.

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

Affiliations

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

Stan Benjamens et al. NPJ Digit Med. .

Abstract

At the beginning of the artificial intelligence (AI)/machine learning (ML) era, the expectations are high, and experts foresee that AI/ML shows potential for diagnosing, managing and treating a wide variety of medical conditions. However, the obstacles for implementation of AI/ML in daily clinical practice are numerous, especially regarding the regulation of these technologies. Therefore, we provide an insight into the currently available AI/ML-based medical devices and algorithms that have been approved by the US Food & Drugs Administration (FDA). We aimed to raise awareness of the importance of regulatory bodies, clearly stating whether a medical device is AI/ML based or not. Cross-checking and validating all approvals, we identified 64 AI/ML based, FDA approved medical devices and algorithms. Out of those, only 29 (45%) mentioned any AI/ML-related expressions in the official FDA announcement. The majority (85.9%) was approved by the FDA with a 510(k) clearance, while 8 (12.5%) received de novo pathway clearance and one (1.6%) premarket approval (PMA) clearance. Most of these technologies, notably 30 (46.9%), 16 (25.0%), and 10 (15.6%) were developed for the fields of Radiology, Cardiology and Internal Medicine/General Practice respectively. We have launched the first comprehensive and open access database of strictly AI/ML-based medical technologies that have been approved by the FDA. The database will be constantly updated.

Keywords: Health services; Outcomes research.

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Conflict of interest statement

Competing interestsThe authors declare no competing interests.

Figures

Fig. 1
Fig. 1. An infographic about the 29 FDA-approved, AI/ML-based medical technologies.
The devices have features such as date and type of FDA approval; name of the device, its short description and which primary and secondary medical specialty it is related to.
Fig. 2
Fig. 2
Flowchart for the selection of AI/ML-based algorithms for this online database, including the number of identified webpages, the number of screened announcements, the number of eligible devices and algorithms, and the final number of included AI/ML-based devices and algorithms.

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