REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

ABSTRACT:

Background

Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples.

Methods

We applied natural language process (NLP) methods for analyzing 30,235 in-house historical clinical reports through active learning, and then, developed clinical knowledge bases, evidence-based interpretation methods and reporting criteria to support the whole postdetection pipeline.

Results

Of the 30,235 reports, we obtained 37,175 CNV-paragraph pairs. For these pairs,

SUBMITTER: Liu M 

PROVIDER: S-EPMC7667294 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature