Automatic Cohort

Automatic cohort creation aims to automate the process of identifying and selecting groups of individuals sharing specific characteristics, streamlining tasks like clinical trial recruitment and disease research. Current research focuses on developing algorithms and models, including those leveraging large language models and novel neural network architectures, to efficiently extract relevant cohorts from diverse data sources, such as electronic health records and event streams, using both structured and unstructured data. This automation promises to significantly improve the efficiency and reproducibility of healthcare research, enabling more robust and equitable studies while reducing the time and cost associated with manual cohort identification.