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In online forums like Reddit, users share their experiences with medicalconditions and treatments, including making claims, asking questions, anddiscussing the effects of treatments on their health. Building systems tounderstand this information can effectively monitor the spread ofmisinformation and verify user claims. The Task-8 of the 2023 InternationalWorkshop on Semantic Evaluation focused on medical applications, specificallyextracting patient experience- and medical condition-related entities from userposts on social media. The Reddit Health Online Talk (RedHot) corpus containsposts from medical condition-related subreddits with annotations characterizingthe patient experience and medical conditions. In Subtask-1, patient experienceis characterized by personal experience, questions, and claims. In Subtask-2,medical conditions are characterized by population, intervention, and outcome.For the automatic extraction of patient experiences and medical conditioninformation, as a part of the challenge, we proposed language-model-basedextraction systems that ranked $3^{rd}$ on both subtasks' leaderboards. In thiswork, we describe our approach and, in addition, explore the automaticextraction of this information using domain-specific language models and theinclusion of external knowledge.

MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions,  Experiences and Claims from Social Media using Knowledge-Augmented  Pre-trained Language Models