Clinical Named Entity Recognition

Clinical Named Entity Recognition (NER) focuses on automatically identifying and classifying key medical entities (diseases, medications, procedures, etc.) within unstructured clinical text, aiming to improve information extraction for tasks like automated coding and clinical decision support. Current research emphasizes improving the performance of large language models (LLMs) and transformer-based architectures on this task, particularly addressing challenges posed by imbalanced datasets and the need for precise token-level recognition. This work is crucial for advancing healthcare informatics by enabling efficient processing of large volumes of clinical data, facilitating more accurate diagnoses, and supporting the development of personalized medicine.