Extraction of determinants of postoperative length of stay from operation records

Takanori Yamashita, Yoshifumi Wakata, Naoki Nakashima, Sachio Hirokawa, Satoshi Hamai, Yasuharu Nakashima, Yukihide Iwamoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Secondary use of clinical text data are gaining much attention in improving the quality and the efficiency of medical treatment. Although there is some case studies of medical-examination text data, there are not many examples fed back to the medical-examination spot. The present paper analyses the operation records of total hip arthroplasty. We extracted feature words that characterize the two peaks which appeared in distribution of postoperative hospital days using SVM (support vector machine) and FS (feature selection). The models gained by optimal FS attained 60% accuracy as prediction performance. We applied logistic regression analysis to estimate postoperative length of stay from the extracted feature words. Most words were not statistically significant except two words.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Workshop on Electronics, Computer and Applications, IWECA 2014
PublisherIEEE Computer Society
Pages822-827
Number of pages6
ISBN (Print)9781479945658
DOIs
Publication statusPublished - 2014
Event2014 IEEE Workshop on Electronics, Computer and Applications, IWECA 2014 - Ottawa, ON, Canada
Duration: May 8 2014May 9 2014

Publication series

NameProceedings - 2014 IEEE Workshop on Electronics, Computer and Applications, IWECA 2014

Other

Other2014 IEEE Workshop on Electronics, Computer and Applications, IWECA 2014
Country/TerritoryCanada
CityOttawa, ON
Period5/8/145/9/14

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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