Cell recognition based on features extracted by AFM and parameter optimization classifiers-Reference-Cited by-同舟云学术

Cell recognition based on features extracted by AFM and parameter optimization classifiers

Published:2024 Issue:27 Volume:16 Page:4626-4635
ISSN:1759-9660
Container-title:Analytical Methods
language:en
Short-container-title:Anal. Methods

Author:

Wang Junxi¹²³⁴,Yang Fan¹²³⁴,Wang Bowei¹²³⁴,Hu Jing¹²³,Liu Mengnan¹²³,Wang Xia¹²³⁴,Dong Jianjun¹²³⁴,Song Guicai⁴,Wang Zuobin¹²³⁴⁵^ORCID

Affiliation:

1. International Research Centre for Nano Handling and Manufacturing of China, Changchun University of Science and Technology, Changchun 130022, China

2. Centre for Opto/Bio-Nano Measurement and Manufacturing, Zhongshan Institute of Changchun University of Science and Technology, Zhongshan 528400, China

3. Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing, Changchun University of Science and Technology, Changchun 130022, China

4. College of Physics, Changchun University of Science and Technology, Changchun 130022, China

5. JR3CN & IRAC, University of Bedfordshire, Luton LU1 3JU, UK

Abstract

This study employed an atomic force microscope (AFM) to characterize the morphological and mechanical properties of four cell lines. Then a cell recognition method based on machine learning and feature engineering was proposed.

Funder

Natural Science Foundation of Jilin Province

National Key Research and Development Program of China

National Natural Science Foundation of China

HORIZON EUROPE Framework Programme

Department of Science and Technology of Jilin Province

Higher Education Discipline Innovation Project

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/AY/D4AY00684D

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