Utility of Features in a Natural-Language-Processing-Based Clinical De-Identification Model Using Radiology Reports for Advanced NSCLC Patients

• Published in: Applied sciences Vol. 12; no. 19; p. 9976
• Main Authors: Paul, Tanmoy, Islam, Humayera, Singh, Nitesh, Jampani, Yaswitha, Kotapati, Teja Venkat Pavan, Tautam, Preethi Aishwarya, Rana, Md Kamruz Zaman, Mandhadi, Vasanthi, Sharma, Vishakha, Barnes, Michael, Hammer, Richard D., Mosa, Abu Saleh Mohammad
• Format: Journal Article
• Language: English
• Published: MDPI AG 01.10.2022
• Subjects: conditional random field (CRF); de-identification; named entity recognition (NER); natural language processing (NLP); protected health information

The de-identification of clinical reports is essential to protect the confidentiality of patients. The natural-language-processing-based named entity recognition (NER) model is a widely used technique of automatic clinical de-identification. The performance of such a machine learning model relies la...