Description:
This dataset comprises multiple-choice questions from the "Educational Review" articles published by the journal Pediatric Nephrology between January 2014 and April 2024. Each entry in the dataset includes the context of the question, the question itself, and the correct answer. This dataset is designed to evaluate the performance of large language models (LLMs) like ChatGPT-4o and Gemini 1.5 in the field of pediatric nephrology.
Had Collaborated: Pierluigi Marzuillo MD, Vittoria Frattolillo MD, Simone Colosimo MD, Alessandra Perrotta MD

Dataset Structure:

Context: A brief summary or excerpt from the article providing context for the question.
Question: The multiple-choice question extracted from the "Educational Review" articles.
Answer: The correct answer to the multiple-choice question.
Columns:

Context: Text providing background information relevant to the question.
Question: The question presented to the model, formatted to include the multiple-choice options.
Answer: The correct answer option (e.g., 'A', 'B', 'C', 'D') as provided in the article.
Example Entry:

Context: "Aliskiren, the first direct renin inhibitor: an update on its mechanism of action, side effects, and clinical use in pediatric patients."
Question: "The mechanism of action of aliskiren to improve blood pressure in pediatric patients includes: <br> a. Inhibiting the conversion of angiotensinogen to angiotensin I <br> b. Blocking the angiotensin II receptor <br> c. Inhibiting the conversion of angiotensin I to angiotensin II <br> d. Blocking aldosterone synthesis"
Answer: "C"