Investigation of the Utility of Features in a Clinical De-identification Model: A Demonstration Using EHR Pathology Reports for Advanced NSCLC Patients

• Main Authors: Tanmoy Paul (Author), Md Kamruz Zaman Rana (Author), Preethi Aishwarya Tautam (Author), Teja Venkat Pavan Kotapati (Author), Yaswitha Jampani (Author), Nitesh Singh (Author), Humayera Islam (Author), Vasanthi Mandhadi (Author), Vishakha Sharma (Author), Michael Barnes (Author), Richard D. Hammer (Author), Abu Saleh Mohammad Mosa (Author)
• Format: Book
• Published: Frontiers Media S.A., 2022-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundElectronic health record (EHR) systems contain a large volume of texts, including visit notes, discharge summaries, and various reports. To protect the confidentiality of patients, these records often need to be fully de-identified before circulating for secondary use. Machine learning (ML...