Direct cellularity estimation on breast cancer histopathology images using transfer learning

DOI10.1155/2019/3041250zbMath1423.92171DBLPjournals/cmmm/PeiCLC19OpenAlexW2949003314WikidataQ91689192 ScholiaQ91689192MaRDI QIDQ2003647

Ziang Pei, Lijun Lu, Shuangliang Cao, Wu-Fan Chen

Publication date: 9 July 2019

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2019/3041250

zbMATH Keywords

transfer learningbreast cancer histopathology imagescellularity estimation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Biomedical imaging and signal processing (92C55) Computational methods for problems pertaining to biology (92-08)

Uses Software

• LIBSVM
• Scikit
• XGBoost
• ImageNet
• LightGBM
• Xception

Cites Work

• Greedy function approximation: A gradient boosting machine.
• A NEW MEASURE OF RANK CORRELATION
• THE TREATMENT OF TIES IN RANKING PROBLEMS
• Unnamed Item
• Unnamed Item

This page was built for publication: Direct cellularity estimation on breast cancer histopathology images using transfer learning