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

Breast Cancer (201) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Natural Language Processing (650) Infodemiology and Infoveillance (1278) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015)

Published on in Vol 8, No 2 (2022): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37840, first published .
Extracting Multiple Worries From Breast Cancer Patient Blogs Using Multilabel Classification With the Natural Language Processing Model Bidirectional Encoder Representations From Transformers: Infodemiology Study of Blogs

Extracting Multiple Worries From Breast Cancer Patient Blogs Using Multilabel Classification With the Natural Language Processing Model Bidirectional Encoder Representations From Transformers: Infodemiology Study of Blogs

Extracting Multiple Worries From Breast Cancer Patient Blogs Using Multilabel Classification With the Natural Language Processing Model Bidirectional Encoder Representations From Transformers: Infodemiology Study of Blogs

Authors of this article:

Tomomi Watanabe1 Author Orcid Image ;   Shuntaro Yada2 Author Orcid Image ;   Eiji Aramaki2 Author Orcid Image ;   Hiroshi Yajima3 Author Orcid Image ;   Hayato Kizaki1 Author Orcid Image ;   Satoko Hori1 Author Orcid Image
Article Authors Cited by (7) Tweetations (9) Metrics

Tomomi Watanabe   1 , BSc ;   Shuntaro Yada   2 , PhD ;   Eiji Aramaki   2 , PhD ;   Hiroshi Yajima   3 , MSc ;   Hayato Kizaki   1 , MSc ;   Satoko Hori   1 , PhD

1 Division of Drug Informatics, Keio University Faculty of Pharmacy, Tokyo, Japan

2 Nara Institute of Science and Technology, Nara, Japan

3 Mediaid Corporation, Tokyo, Japan

Corresponding Author:

  • Satoko Hori, PhD
  • Division of Drug Informatics
  • Keio University Faculty of Pharmacy
  • 1-5-30 Shibakouen, Minato-ku
  • Tokyo, 105-8512
  • Japan
  • Phone: 81 3-5400-2650
  • Email: hori-st@pha.keio.ac.jp