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

Decision Support for Health Professionals (1210) Safety and Error Prevention in Health (206) Electronic Health Records (1068) Machine Learning (1501) Natural Language Processing (706) Falls Prevention in the Elderly (72) Nursing in a Hospital Setting (104) Nursing Records (14)

Published on in Vol 8, No 4 (2020): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16970, first published .
Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Authors of this article:

Hayao Nakatani1 Author Orcid Image ;   Masatoshi Nakao1 Author Orcid Image ;   Hidefumi Uchiyama2, 3 Author Orcid Image ;   Hiroyoshi Toyoshiba3 Author Orcid Image ;   Chikayuki Ochiai1, 4 Author Orcid Image
Article Authors Cited by (38) Tweetations (2) Metrics

Hayao Nakatani   1 , MD, PhD ;   Masatoshi Nakao   1 , RN, MA ;   Hidefumi Uchiyama   2, 3 , PhD ;   Hiroyoshi Toyoshiba   3 , PhD ;   Chikayuki Ochiai   1, 4 , MD, PhD

1 NTT Medical Center Tokyo, Tokyo, Japan

2 Pharmaceutical Research Department, Global Pharmaceutical R&D Division, Neopharma Japan Co Ltd, Tokyo, Japan

3 Research Development Department, Lifescience AI Business Division, FRONTEO Inc, Tokyo, Japan

4 Tokyo Healthcare University, Tokyo, Japan

Corresponding Author:

  • Hidefumi Uchiyama, PhD
  • Pharmaceutical Research Department
  • Global Pharmaceutical R&D Division
  • Neopharma Japan Co Ltd
  • Iidabashi Grand Bloom 4F
  • 2-10-2 Fujimi, Chiyoda-ku
  • Tokyo, 102-0071
  • Japan
  • Phone: 81 90-3896-2658
  • Email: huchiyam@gmail.com