| Autor: |
Ghanawi, Ibrahim, Chami, Mohammad Wissam, Chami, Mohammad, Coric, Marko, Abdoun, Nabil |
| Předmět: |
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| Zdroj: |
Incose International Symposium; Jul2024, Vol. 34 Issue 1, p1354-1366, 13p |
| Abstrakt: |
The growing adoption of Model‐Based Systems Engineering (MBSE) in the medical sector has prompted a significant emphasis on the digitization of medical standards into norm models. This transformation promotes consistency and allows for tracing system model elements to the corresponding norm model elements. Despite these efforts, the current digitization activities heavily rely on manual extraction and transformation, particularly from PDF documents into SysML models. Concurrently, the proliferation of Artificial Intelligence (AI) applications in recent years presents an opportunity to automate such activities. This paper contributes to the integration of AI with MBSE, focusing solely on the extraction and transformation of medical standards information from documents into SysML norm models. It explores the initial outcomes of augmenting data extraction from medical standards using recent AI algorithms and integrating them into MBSE practices. The evaluation involves two approaches, an open‐source multimodal classifier model and a proprietary large language model. The study assesses these approaches on a medical standard and outlines future work, including the exploration of an open‐source large language model approach. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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