Clinical Code

Clinical code prediction automates the assignment of standardized medical codes (like ICD codes) to unstructured clinical text, reducing the time and error associated with manual coding. Current research focuses on improving accuracy using deep learning architectures, such as transformers, graph neural networks, and various autoencoder approaches, often incorporating auxiliary information like drug prescriptions or temporal context from multiple patient notes. These advancements aim to enhance the efficiency and accuracy of medical record management, facilitating better patient care, improved clinical research, and streamlined healthcare reimbursement processes.