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Assuring Intelligent Medical Devices: AI Assurance Cases.

Anita Khadka¹, Gregory Epiphaniou¹, Carsten Maple¹

¹University of Warwick, Coventry, UK.

Studies in Health Technology and Informatics

|July 1, 2025

Summary

This summary is machine-generated.

Artificial Intelligence (AI) and Machine Learning (ML) enhance medical devices but pose challenges. Structured assurance case patterns are proposed to ensure trustworthy AI-enabled medical systems by addressing risks like data integrity and regulatory compliance.

Keywords:

AI Assurance Intelligent Medical Devices Regulatory Compliance

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Area of Science:

Medical Device Engineering
Artificial Intelligence in Healthcare
Machine Learning for Medical Applications

Background:

Integration of AI and ML in medical devices offers significant advancements in automation, precision, and efficiency.
These technologies introduce complex challenges including data integrity, algorithmic transparency, adversarial robustness, and regulatory compliance.
Existing assurance methods are inadequate for the dynamic nature of AI-driven medical systems.

Purpose of the Study:

To address the challenges posed by AI/ML in medical devices.
To propose structured assurance case patterns specifically designed for AI-enabled medical devices.
To enhance the trustworthiness of intelligent medical systems.

Main Methods:

Discussion of a wide range of structured assurance case patterns.
Exploration of potential risks associated with ML-based medical systems.
Design of assurance cases to mitigate identified risks.

Main Results:

Identification of key challenges in AI/ML medical device assurance.
Development of tailored assurance case patterns for AI-enabled devices.
Framework for building trustworthy AI-driven medical systems.

Conclusions:

Structured assurance cases are crucial for validating AI/ML in medical devices.
Addressing risks like data integrity and robustness is essential for regulatory compliance.
The proposed patterns facilitate the development of reliable and trustworthy intelligent medical systems.