ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports

Abstract Introduction Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classification of diseases (ICD) codes which are inaccurate – leading to mi...

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Bibliographic Details
Main Authors: Jeffrey Wang, Joao Souza de Vale, Saransh Gupta, Pulakesh Upadhyaya, Felipe A. Lisboa, Seth A. Schobel, Eric A. Elster, Christopher J. Dente, Timothy G. Buchman, Rishikesan Kamaleswaran
Format: Article
Language:English
Published: BMC 2023-11-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Natural language processing
Machine learning
Venous thromboembolism
Online Access:https://doi.org/10.1186/s12911-023-02369-z

Internet

https://doi.org/10.1186/s12911-023-02369-z

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