Clinical Application

Clinical application of artificial intelligence, particularly large language models (LLMs) and deep learning, is a rapidly evolving field focused on improving healthcare delivery and patient outcomes. Current research emphasizes developing and validating AI models for tasks such as diagnosis support, patient education, and image analysis, often employing architectures like U-Net, 3D nnU-Net, and graph convolutional networks. This work highlights the need for robust evaluation frameworks, addressing issues like model interpretability, bias, and generalizability across diverse datasets to ensure safe and effective clinical implementation. The ultimate goal is to leverage AI's potential to enhance diagnostic accuracy, personalize treatment, and improve efficiency in various medical specialties.