FDA Approved AI products
Highlights from the report
- Radiology has experienced the steadiest increase of AI/ML-enabled device submissions of any specialty.
- Machine learning models have ranged in complexity from shallow (less than two hidden layers) models to more complex models (deep learning models).
- In general, models have increasingly adopted hybrid approaches, integrating diverse algorithmic methods to attain the outcome of a secure and efficient device. This might involve employing one model for feature generation and another for classification, for instance.
- The list covers a period between 1995-2023.
- As anticipated, there has been a notable increase in FDA approvals for devices empowered by AI/ML since 2020, following the onset of the COVID-19 pandemic.
The compilation comprises information that is publicly accessible regarding devices empowered by AI/ML.
As technology relentlessly propels healthcare into the future, artificial intelligence (AI) and its machine learning (ML) subset are becoming integral components of an expanding array of medical devices. The real magic lies in AI/ML’s capacity to extract novel insights from the immense volume of healthcare data generated daily. In this era of digital health, where technology is reshaping our lives, AI/ML emerges as a driving force, propelling substantial progress.
Over the past decade, the FDA has greenlit an increasing number of AI/ML devices spanning diverse medical domains, a trend expected to persist. Notably, as of October 19, 2023, no device has gained authorization leveraging generative AI, artificial general intelligence (AGI), or harnessing the power of large language models. The landscape of AI/ML in medical devices is ever-evolving, promising exciting advancements while the FDA remains vigilant in upholding its public health mission.