Integrated Natural Language Processing and Machine Learning Models for Standardizing Radiotherapy Structure Names.

ABSTRACT: The lack of standardized structure names in radiotherapy (RT) data limits interoperability, data sharing, and the ability to perform big data analysis. To standardize radiotherapy structure names, we developed an integrated natural language processing (NLP) and machine learning (ML) based system that can map the physician-given structure names to American Association of Physicists in Medicine (AAPM) Task Group 263 (TG-263) standard names. The dataset consist of 794 prostate and 754 lung cancer patients across the 40 different radiation therapy centers managed by the Veterans Health Administration (VA). Additionally, data from the Radiation Oncology department at Virginia Commonwealth University (VCU) was collected to serve as a test set. Domain experts identified as anatomically significan

SUBMITTER: Syed K 

PROVIDER: S-EPMC7348919 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature