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

Breast Cancer (244) Natural Language Processing (801) Emotional, Social, Psychological Support for Cancer (215) Patient Education for Cancer (188) Information Seeking, Information Needs (525) Infodemiology and Infoveillance (1454)

Published on in Vol 7, No 4 (2021): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32005, first published .
Medical Needs Extraction for Breast Cancer Patients from Question and Answer Services: Natural Language Processing-Based Approach

Medical Needs Extraction for Breast Cancer Patients from Question and Answer Services: Natural Language Processing-Based Approach

Medical Needs Extraction for Breast Cancer Patients from Question and Answer Services: Natural Language Processing-Based Approach

Authors of this article:

Masaru Kamba1 Author Orcid Image ;   Masae Manabe1 Author Orcid Image ;   Shoko Wakamiya1 Author Orcid Image ;   Shuntaro Yada1 Author Orcid Image ;   Eiji Aramaki1 Author Orcid Image ;   Satomi Odani2 Author Orcid Image ;   Isao Miyashiro2 Author Orcid Image
Article Authors Cited by (4) Tweetations (5) Metrics

Journals

  1. Tong C, Margolin D, Chunara R, Niederdeppe J, Taylor T, Dunbar N, King A. Search Term Identification Methods for Computational Health Communication: Word Embedding and Network Approach for Health Content on YouTube. JMIR Medical Informatics 2022;10(8):e37862 View
  2. Jiao J, Chen Y, Li Z, Weng T. AWDS-net: automatic whole-field segmentation network for characterising diverse breast masses. Connection Science 2024;36(1) View
  3. Nie L, Xu J, Wang R, Tilga H. Health information needs and feedback of users in the online TCM community. PLOS ONE 2024;19(3):e0301536 View
  4. Zhang Z, Liew K, Kuijer R, She W, Yada S, Wakamiya S, Aramaki E. Differing Content and Language Based on Poster-Patient Relationships on the Chinese Social Media Platform Weibo: Text Classification, Sentiment Analysis, and Topic Modeling of Posts on Breast Cancer. JMIR Cancer 2024;10:e51332 View