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

Yukiko Ohno Riri Kato Haruki Ishikawa Tomohiro Nishiyama Minae Isawa Mayumi Mochizuki Eiji Aramaki Tohru Aomori

Published in: JMIR formative research (2024)

MedNER-J successfully read pharmaceutical care records and showed the best performance for assessment data. However, challenges remain in analyzing records other than assessment data. Therefore, it will be necessary to reinforce the training data for subjective data in order to apply the system to pharmaceutical care records.

Keyphrases

healthcare
electronic health record
palliative care
big data
quality improvement
autism spectrum disorder
affordable care act
machine learning
depressive symptoms
physical activity
chronic pain
clinical evaluation