Medical terminology is perceived as an obstacle for patients and family members to understand the medical message. In this context, plain language advocates for making specialised knowledge accessible to citizens. This article puts the synergy between medical terminology, plain language, and computational linguistics (a branch of Artificial Intelligence) on the table. Our purpose is to determine if Generative AI applications, like ChatGPT, can assist in creating glossaries of terms with their corresponding simple variants. For this, a relevant sub-field of medicine, cardiology, was taken as a case study, even though it could be extrapolated to other sub-fields. Next, a glossary of key cardiology terms was created following a classic methodological approach. Then, the most relevant phases of the process (terminology extraction, search for synonyms, and selection of the clearest synonym) were reproduced using ChatGPT. The results of the comparative study between both approaches give a glimpse of the extent to which this technology can be a useful resource for creating glossaries that can be employed for writing using plain language., This research project was funded by a Margarita Salas postdoctoral contract thanks to the European Union-NextGenerationEU, Ministry of Science, Innovation and Universities of the Spanish Government, and Recovery, Transformation and Resilience Plan, through a call from Pompeu Fabra University (Barcelona). This article is also supported by the grant 'A technological prototype for writing in plain language: incorporation in public administration and analysis of its impact on citizens (arText_IMPACT)' (PDC2022-133935-I00), funded by MICIU/AEI /10.13039/501100011033 and by the 'European Union NextGenerationEU/PRTR'.