This paper is in the following e-collection/theme issue:

Patient-Reported Outcome Measures (PROMs) (372) Natural Language Processing (917) Machine Learning (2076) Ontologies, Classifications, and Coding (324) Artificial Intelligence (2129) Pain in Children and Adolescents (58) Children and Young People With Cancer, Pediatric Oncology (78)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26777, first published .
Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study

Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study

Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study

Authors of this article:

Zhaohua Lu1 Author Orcid Image ;   Jin-ah Sim2, 3 Author Orcid Image ;   Jade X Wang1 Author Orcid Image ;   Christopher B Forrest4 Author Orcid Image ;   Kevin R Krull2 Author Orcid Image ;   Deokumar Srivastava1 Author Orcid Image ;   Melissa M Hudson5 Author Orcid Image ;   Leslie L Robison2 Author Orcid Image ;   Justin N Baker5 Author Orcid Image ;   I-Chan Huang2 Author Orcid Image
Article Authors Cited by (31) Tweetations (15) Metrics

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  3. Li S, Deng L, Zhang X, Chen L, Yang T, Qi Y, Jiang T. Deep Phenotyping of Chinese Electronic Health Records by Recognizing Linguistic Patterns of Phenotypic Narratives With a Sequence Motif Discovery Tool: Algorithm Development and Validation. Journal of Medical Internet Research 2022;24(6):e37213 View
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  7. Sim J, Huang X, Horan M, Stewart C, Robison L, Hudson M, Baker J, Huang I. Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review. Artificial Intelligence in Medicine 2023;146:102701 View
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  19. Tashtoush N, Al-Ghraibah A, Azhar Syed Sulaiman S, Anis Amran F, Khairizan Rahim S, Noor Harun S. Cancer pain detection based on physiological parameters and machine learning. Cogent Engineering 2024;11(1) View
  20. Zhang L, Yu H, Li J, Huang L, Cheng S, Xiao J. Data – Knowledge driven machine learning model for cancer pain medication decisions. International Journal of Medical Informatics 2025;195:105727 View
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