Pneumonia remains a significant global health challenge, contributing to high mortality rates, particularly among vulnerable populations such as children and the elderly. Early and accurate diagnosis is critical, as delayed intervention can lead to severe complications. This research focuses on advancing automated medical image captioning to assist in pneumonia detection, leveraging large language models and generative AI to bridge gaps in clinical interpretation and decision-making. The work aims to enhance diagnostic accuracy and reduce reliance on manual interpretation by integrating state-of-the-art methods for image feature extraction and captioning. Preliminary results suggest that the GPT-4 model outperforms existing approaches, achieving superior accuracy and contextual relevance in generating clinically meaningful captions.