Python-based Risk Classification Tool for Medical Devices

Abstract

This paper presents a Python-based risk classification tool specifically designed for medical devices, aimed at streamlining the assessment process and enhancing decision-making capabilities for healthcare professionals and regulatory bodies. The paper addresses existing regulatory gaps in Software as a Medical Device (SaMD) regulation, highlighting the challenges faced by stakeholders in ensuring compliance and safety and offers this tool as a suggestion for improvement. Leveraging advanced machine learning algorithms, the tool analyzes various risk factors associated with medical devices, including design, usage, and potential failure modes. By providing a scalable solution for risk classification, this work aims to bridge the gap between technological advancements and regulatory frameworks, ultimately fostering a safer healthcare environment.