Clinical Setting

Clinical settings are increasingly leveraging artificial intelligence (AI) to improve efficiency and accuracy in diagnosis, treatment, and patient care. Current research focuses on developing and validating AI models, including convolutional neural networks (CNNs), transformers, and large language models (LLMs), for tasks such as medical image analysis, natural language processing of clinical notes, and automated sleep scoring. These advancements aim to enhance diagnostic capabilities, streamline workflows, and ultimately improve patient outcomes, though challenges remain in ensuring model generalizability, reliability, and integration into existing clinical practices.