A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation.

Xiaoqian Jiang Liwei Wang Huan He Sunyang Fu Sijia Liu David A Hanauer Daniel R Harris Ramakanth Kavuluru Rui Zhang Karthik Natarajan Nishanth P Pavinkurve Janos G Hajagos Sritha Rajupet Veena Lingam Mary Saltz Corey Elowsky Richard A Moffitt Farrukh M Koraishy Matvey B Palchuk Jordan Donovan Lora Lingrey Garo Stone-DerHagopian Robert T Miller Andrew E Williams Peter J Leese Paul I Kovach Emily Rose Pfaff Mikhail Zemmel Robert D Pates Nick Guthe Melissa A Haendel Christopher G Chute Hongfang Liunull nullnull null

Published in: JMIR medical informatics (2024)

The evolutionary and time-critical nature of the PASC NLP task significantly complicates existing approaches to NLP algorithm development. In this work, we present a hybrid approach using the Open Health Natural Language Processing Toolkit aimed at addressing these needs with a dictionary-based weak labeling step that minimizes the need for additional expert annotation while still preserving the fine-tuning capabilities of expert involvement.

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