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

• Автори: Tanmoy Paul (Автор), Md Kamruz Zaman Rana (Автор), Preethi Aishwarya Tautam (Автор), Teja Venkat Pavan Kotapati (Автор), Yaswitha Jampani (Автор), Nitesh Singh (Автор), Humayera Islam (Автор), Vasanthi Mandhadi (Автор), Vishakha Sharma (Автор), Michael Barnes (Автор), Richard D. Hammer (Автор), Abu Saleh Mohammad Mosa (Автор)
• Формат: Книга
• Опубліковано: Frontiers Media S.A., 2022-02-01T00:00:00Z.
• Предмети: article
• Онлайн доступ: 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...