Sara Ali F2018242229 Zarmeen Tahir F2018242191 Atrubah Aslam F2018242074 Bashair Ashraf F20182422282025-10-082025-10-082023https://escholar.umt.edu.pk/handle/123456789/8291In the realm of healthcare, the arrival of Artificial Intelligence (AI) has introduced a paradigm shift, redefining the ways medical information is generated. A notable AI application in this domain is ChatGPT, an advanced language model that offers information and assistance on a wide array of topics, including nutritional advice. As AI becomes increasingly linked with healthcare, there emerges a critical need to evaluate the accuracy and reliability of AI-generated data, particularly in contexts as complex as managing hypertension. This study conducts a thematic analysis to evaluate the alignment between ChatGPT-generated data and evidence-based literature. By investigating 15 questions about nutritional approaches for the management of hypertension, this study aims to reveal the similarities and differences between ChatGPT generated data and evidence-based data such as PEN knowledge pathways, PubMed, and Google Scholar.enThesis