IEEE International Conference on Digital Health (ICDH) , 2024 at IEEE World Congress on Services 2024

Semantically Rich Approach to Automating Regulations of Medical Devices

Subhankar Chattoraj and Karuna Pande Joshi

July 11, 2024

Advanced medical devices increasingly use sophisticated AI/ML models to enable real-time analytics for monitoring patients. In the US, these AI models, which often form the underlying device software, are regulated by the Center for Devices & Radiological Health (CDRH) at the Food & Drug Administration (FDA) to ensure the safety & efficacy of the medical device. These regulations for medical devices are currently available as large textual documents, called Code of Federal Regulations (CFR) Title 21, that cross-reference other documents & so require substantial human effort to parse & comprehend. Hence, the device manufacturers incur significant costs during the regulatory process to adhere to all the rules & policies laid down by the FDA. We have developed a novel, semantically rich approach to extract the knowledge from the rules & policies for Medical devices & translate it into a machine-processable format that can be reasoned over. This framework was developed using AI/Knowledge Management approaches & Semantic Web technologies like OWL/RDF & SPARQL. This paper presents the detailed Ontology/Knowledge graph we developed for medical device regulations & the Use case results that validate our design. Regulators & manufacturers alike can use our framework to significantly reduce the human effort required during the device regulatory process.

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Tags: semantic web; knowledge graph; medical device; compliance; code of federal regulations.

Type: InProceedings

Publisher: IEEE

Organization: IEEE

Downloads: 288 downloads