Assessing the Utilization of Large Language Model Chatbots for Educational Purposes by Medical Teachers: A Nationwide Survey From India.

Background Large language models (LLMs) are increasingly explored in healthcare and education. In medical education, they hold the potential to enhance learning by supporting personalized teaching, resource development, and student engagement. However, LLM use also raises concerns about ethics, accuracy, and reliance.

Role of vitamin D and leptin levels in PCOS in young women: A family medicine perspective.

Introduction: Adolescent girls and young women of childbearing age are the main populations affected by endocrinopathy known as polycystic ovarian syndrome (PCOS). It is especially important to take into account whether clinical and biochemical signs of hyperandrogenism are present in female patients. In maintaining metabolic homeostasis, leptin is crucial.

Quality of life among community-dwelling elderly in rural and urban areas of Himalayan region, Northeast India: An analysis of factors affecting well-being.

Background: There is a dearth of literature on the quality of life (QOL) experienced by the elderly population in the hilly terrains of the Himalayan region. The objective of this study was to highlight the QOL among community-dwelling elderly residing in rural and urban areas of the Himalayan region, Northeast India.

Materials And Method: A cross-sectional study was conducted involving 450 participants (324 in rural and 126 in urban areas) aged 60 years and above.

Clinical Relevance of Sternal Foramina: A Morphometric Study.

Objectives: The present study aimed at determining the incidence of sternal foramina in adult dry bones of North Indian descent. We also aimed to determine the number, precise location of the sternal foramina with a standard reference point which might have considerable importance with regard to procedures involving sternal puncture.

Methods: This cross sectional descriptive study was conducted on 72 dry adult human sternums.

Assessing the Utilization of Large Language Models in Medical Education: Insights From Undergraduate Medical Students.

Background Artificial intelligence (AI) has the potential to be integrated into medical education. Among AI-based technology, large language models (LLMs) such as ChatGPT, Google Bard, Microsoft Bing, and Perplexity have emerged as powerful tools with capabilities in natural language processing. With this background, this study investigates the knowledge, attitude, and practice of undergraduate medical students regarding the utilization of LLMs in medical education in a medical college in Jharkhand, India.