Artificial intelligence to organize patient portal messages: A journey from an ensemble deep learning text classification to rule-based named entity recognition

Ahmad P. Tafti, Sunyang Fu, Aditya Khurana, George M. Mastorakos, Kenneth G. Poole, Stephen J. Traub, James A. Yiannias, Hongfang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Since the turn of the millennium, numerous healthcare venues all over the world have made a standard of communication transition from the classic telephone call to a sophisticated online patient portal system. More and more, a majority of patients prefer using portal-style communication for clinician contact, checking lab results, and other informational transactions, in which hundreds of thousands of patient portal messages (PPMs) are daily generated as free-text data with multiple requests often buried in one single message. Thus, there is a pressing need to design and implement artificial intelligence (AI) algorithms to accurately organize this wealth of data in a timely fashion. With the present contribution, an attempt was made to first develop an ensemble deep learning text classification component and then integrate it with rule-based named entity recognition to categorize free-text PPMs submitted under the 'Non-Urgent Medical Question' subject in the patient portal as either containing active symptom descriptions or logistical requests (e.g., appointment rescheduling).

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
EditorsIllhoi Yoo, Jinbo Bi, Xiaohua Tony Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1380-1387
Number of pages8
ISBN (Electronic)9781728118673
DOIs
StatePublished - Nov 2019
Event2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States
Duration: Nov 18 2019Nov 21 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Conference

Conference2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
CountryUnited States
CitySan Diego
Period11/18/1911/21/19

Keywords

  • ensemble deep learning
  • Patient portal messages
  • text analytics
  • text classification

ASJC Scopus subject areas

  • Biochemistry
  • Biotechnology
  • Molecular Medicine
  • Modeling and Simulation
  • Health Informatics
  • Pharmacology (medical)
  • Public Health, Environmental and Occupational Health

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  • Cite this

    Tafti, A. P., Fu, S., Khurana, A., Mastorakos, G. M., Poole, K. G., Traub, S. J., Yiannias, J. A., & Liu, H. (2019). Artificial intelligence to organize patient portal messages: A journey from an ensemble deep learning text classification to rule-based named entity recognition. In I. Yoo, J. Bi, & X. T. Hu (Eds.), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 (pp. 1380-1387). [8982942] (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM47256.2019.8982942