IDT-Editor: A Web Application for Streamlining Expert Knowledge Acquisition

Abstract

Artificial intelligence has made significant advancements in various domains. However, human knowledge and expertise remain crucial, especially in the medical domain, for effective decision-making. The process of acquiring and converting human expertise into a machine-readable format has proven to be a challenging task. In response to this challenge, we are introducing IDT-Editor, a user-friendly web-based application designed to help experts transform their knowledge into a format compatible with machines. With the assistance of IDT-Editor, experts can easily create decision trees, including Iterative Decision Trees (IDTs), simplifying the visual representation of their knowledge. The knowledge within the IDTs is automatically and seamlessly converted into production rules, which are then subject to expert verification before being stored in a dedicated knowledge repository. This repository subsequently becomes a valuable resource for future decision-making processes.

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