Long Clinical

Long clinical text processing focuses on developing and applying natural language processing (NLP) techniques to analyze extensive patient records, aiming to improve clinical decision-making and healthcare outcomes. Current research emphasizes using advanced transformer models like Longformer and BigBird, designed to handle the length limitations of traditional architectures, along with ensemble methods and federated learning to address data privacy and scalability challenges. This work is significant because it enables more accurate and efficient extraction of information from lengthy clinical documents, potentially leading to improved diagnostic accuracy, personalized treatment plans, and more effective disease prediction.