Natural Language Processing for the Identification of Incidental Lung Nodules in Computed Tomography Reports: A Quality Control Tool

Affiliations

Rodrigo Basilio: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Alysson Roncally Carvalho: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Rosana Rodrigues: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Marco Conrado: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Stefânia Anselmini Accorsi: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Reza Forghani: Radiomics and Augmented Intelligence Laboratory (RAIL), University of Florida, Gainesville, FL
Tiago Machuca: D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
Matheus Zanon: Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil
Stephan Altmayer: Stanford Hospital, Stanford University Medical Center, Palo Alto, CA
Bruno Hochhegger: Radiomics and Augmented Intelligence Laboratory (RAIL), University of Florida, Gainesville, FL

Abstract

NLP tool accurately identifies ILNs in chest CT reports, enabling early lung cancer detection and reducing patient loss to follow-up.

ISSN: 2687-8941 (Online)
Publisher: American Society of Clinical Oncology
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://ascopubs.org/journal/go