Discriminating drug-resistant bacteria using AI analysis on fine current changes from inner ION leakages

Aomi Yoshikawa, Takao Yasui, Taisuke Shimada, Seiji Yamasaki, Kunihiko Nishino, Takeshi Yanagida, Kazuki Nagashima, Takashi Washio, Tomoji Kawai, Yoshinobu Baba

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

As the WHO delivers a strong warning about drug-resistant bacteria, their types are increasing along with improper use of antibiotic drugs by medical professions, due to the fact that conventional methods cannot identify drug-resistant bacteria in a short time, and show a guideline for proper use of antibiotic drugs rapidly. Herein, we demonstrated a rational methodology for drug-resistant bacteria identification via machine learning analysis on fine current changes from bacteria inner ion leakages, which given by highly applied electric fields in microchannels We believe that our methodology opens up a new way for proper use of antibiotic drugs against drug-resistant bacteria.

本文言語英語
ホスト出版物のタイトル23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019
出版社Chemical and Biological Microsystems Society
ページ852-853
ページ数2
ISBN(電子版)9781733419000
出版ステータス出版済み - 2019
イベント23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019 - Basel, スイス
継続期間: 10 27 201910 31 2019

出版物シリーズ

名前23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019

会議

会議23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019
Countryスイス
CityBasel
Period10/27/1910/31/19

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Chemical Engineering (miscellaneous)

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