Topic Models for Automatic Summarization of Patient Records
Primary care physicians (PCPs) are responsible for reviewing and understanding a wide spectrum of a patient's medical history in order to make informed decisions regarding care. However, a variety of factors impede this process, including: the increasing complexity and number of diagnostic tests and treatments, health information exchange standards that may add more information to the medical record, and the need to efficiently see more patients in less time. The use of topic models for summarizing large, unstructured data collections is a growing area of research. This proposal seeks to develop a topic model and ensuing visualization system for automatically summarizing medical records to support PCPs. This project breaks new ground in the use of topic models on clinical data, and will provide future avenues of research in new applications of the proposed topic modeling approach.