Deep learning correlates single-cell morphology with migratory behaviors in microfluidics

Zhixiong Zhang, Lili Chen, Yu Chih Chen, Euisik Yoon

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

Abstract

Metastasis is the major cause of death in breast cancer patients, yet it remains challenging to pinpoint metastatic cancer cells. In this work, we present a comprehensive morphological analysis using deep learning methods including Random Decision Forest (RDF) and Artificial Neural Network (ANN) to establish the correlation between cellular morphology and migration direction/speed.

Original languageEnglish
Title of host publication22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
PublisherChemical and Biological Microsystems Society
Pages331-332
Number of pages2
ISBN (Electronic)9781510897571
Publication statusPublished - 2018
Event22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018 - Kaohsiung, Taiwan, Province of China
Duration: 2018 Nov 112018 Nov 15

Publication series

Name22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
Volume1

Conference

Conference22nd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018
CountryTaiwan, Province of China
CityKaohsiung
Period18/11/1118/11/15

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Bioengineering
  • Chemical Engineering (miscellaneous)
  • Control and Systems Engineering

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