Phenotype Recognition

Phenotype recognition focuses on automatically identifying and classifying observable characteristics (phenotypes) from diverse data sources, such as clinical notes, genomic data, and imaging studies, aiming to improve disease diagnosis, prognosis, and treatment. Current research heavily utilizes large language models (LLMs), including variations of BERT and GPT architectures, often augmented with retrieval methods and ontologies like the Human Phenotype Ontology (HPO), to enhance accuracy and efficiency in phenotype extraction and normalization. These advancements hold significant promise for accelerating biomedical research, enabling more precise disease characterization, and facilitating the development of personalized medicine approaches.