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

Formative Evaluation of Digital Health Interventions (2872) Natural Language Processing (812) Electronic Health Records (1203) Ontologies, Classifications, and Coding (276) Machine Learning (1780) mHealth for Data Collection and Research (1095) Clinical Informatics (1180) Artificial Intelligence (1786) Secondary Use of Clinical Data for Research and Surveillance (425) Development and Evaluation of Research Methods, Instruments and Tools (650)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55798, first published .
Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis

Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis

Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis

Authors of this article:

Yukiko Ohno1 Author Orcid Image ;   Riri Kato1 Author Orcid Image ;   Haruki Ishikawa1 Author Orcid Image ;   Tomohiro Nishiyama2 Author Orcid Image ;   Minae Isawa1 Author Orcid Image ;   Mayumi Mochizuki1 Author Orcid Image ;   Eiji Aramaki2 Author Orcid Image ;   Tohru Aomori3 Author Orcid Image
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JMIR Formative Res: Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis https://t.co/ES6M0SF8Uq https://t.co/dPAltmT1zT

4:10 PM · Jun 04, 2024

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JMIR Formative Research JMIR Formative Research @JMIR_Formative

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