Assessing the Quality and Reliability of AI-Generated Responses to Common Hypertension Queries.

Introduction: The integration of artificial intelligence (AI) in healthcare, particularly through language models like ChatGPT and ChatSonic, has gained substantial attention. This article explores the utilization of these AI models to address patient queries related to hypertension, emphasizing their potential to enhance health literacy and disease understanding. The study aims to compare the quality and reliability of responses generated by ChatGPT and ChatSonic in addressing common patient queries about hypertension and evaluate these AI models using the Global Quality Scale (GQS) and the Modified DISCERN scale.

Evaluating Disparities in Places of Death in the United States Among Patients With Intellectual Disabilities: A 22-Year Analysis Using the CDC-WONDER Database.

Background In the United States, intellectual disabilities are related to higher death rates. Given the relationship between intellectual disabilities and places of death, it is important to evaluate trends and disparities in places of death to direct physician and patient education and improve the chances of patients who will receive end-of-life care to be suitable with their preferences and values. In this study, the data from the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) database was used to examine mortality trends in places of death of patients with intellectual disabilities in the United States between 1999 and 2020.