T-staging pulmonary oncology from radiological reports using natural language processing: translating into a multi-language setting.

ABSTRACT:

Background

In the era of datafication, it is important that medical data are accurate and structured for multiple applications. Especially data for oncological staging need to be accurate to stage and treat a patient, as well as population-level surveillance and outcome assessment. To support data extraction from free-text radiological reports, Dutch natural language processing (NLP) algorithm was built to quantify T-stage of pulmonary tumors according to the tumor node metastasis (TNM) classification. This structuring tool was translated and validated on English radiological free-text reports. A rule-based algorithm to classify T-stage was trained and validated on, respectively, 200 and 225 English free-text radiological reports from diagnostic computed tomography (CT) obtained fo

SUBMITTER: Nobel JM 

PROVIDER: S-EPMC8192634 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature