Published 2024
| Version v2
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A Scoping Review of Health Disparities in FDA-approved AI Medical Devices
Creators
- Muralidharan, Vijaytha
- Adewale, Boluwatife Adeleye
- Huang, Caroline J
- Nta, Mfon Thelma
- Ademiju, Peter Oluwaduyilemi
- Pathmarajah, Pirunthan
- Hang, Man Kien
- Adesanya, Oluwafolajimi
- Abdullateef, Ridwanullah Olamide
- Babatunde, Abdulhammed Opeyemi
- Ajibade, Abdulquddus
- Onyeka, Sonia
- Cai, Zhou Ran
- Daneshjou, Roxana
- Olatunji, Tobi
Description
Machine learning and artificial intelligence (AI/ML) models in healthcare may exacerbate health biases. Regulatory oversight is critical in evaluating the safety and effectiveness of AI/ML devices in clinical settings. We conducted a scoping review on 692 FDA-approved AI/ML-enabled medical devices to examine transparency, safety reporting, and sociodemographic representation. This dataset contains extracted information from 692 Summary of Safety and Effectiveness Documents (SSEDs) of FDA-approved medical devices between 1995 and 2023.
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