Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of
  Biomedical Definitions Generated from Ontological Knowledge
François Remy Thomas Demeester
Background: More than 400,000 biomedical concepts and some of their
relationships are contained in SnomedCT, a comprehensive biomedical ontology.
However, their concept names are not always readily interpretable by
non-experts, or patients looking at their own electronic health records (EHR).
Clear definitions or descriptions in understandable language are often not
available. Therefore, generating human-readable definitions for biomedical
concepts might help make the information they encode more accessible and
understandable to a wider public.
  Objective: In this article, we introduce the Automatic Glossary of Clinical
Terminology (AGCT), a large-scale biomedical dictionary of clinical concepts
generated using high-quality information extracted from the biomedical
knowledge contained in SnomedCT.
  Methods: We generate a novel definition for every SnomedCT concept, after
prompting the OpenAI Turbo model, a variant of GPT 3.5, using a high-quality
verbalization of the SnomedCT relationships of the to-be-defined concept. A
significant subset of the generated definitions was subsequently judged by NLP
researchers with biomedical expertise on 5-point scales along the following
three axes: factuality, insight, and fluency.
  Results: AGCT contains 422,070 computer-generated definitions for SnomedCT
concepts, covering various domains such as diseases, procedures, drugs, and
anatomy. The average length of the definitions is 49 words. The definitions
were assigned average scores of over 4.5 out of 5 on all three axes, indicating
a majority of factual, insightful, and fluent definitions.
  Conclusion: AGCT is a novel and valuable resource for biomedical tasks that
require human-readable definitions for SnomedCT concepts. It can also serve as
a base for developing robust biomedical retrieval models or other applications
that leverage natural language understanding of biomedical knowledge.