Open AccessScaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset
Author(s) -
Hoon Seo,
Lodewijk Brand,
Lucia Saldana Barco,
Hua Wang
Publication year - 2022
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btac267
Subject(s) - support vector machine , computer science , scalability , machine learning , breast cancer , artificial intelligence , quadratic programming , software , cancer , scale (ratio) , data mining , algorithm , pattern recognition (psychology) , medicine , mathematics , mathematical optimization , database , programming language , physics , quantum mechanics
Breast cancer is a type of cancer that develops in breast tissues, and, after skin cancer, it is the most commonly diagnosed cancer in women in the United States. Given that an early diagnosis is imperative to prevent breast cancer progression, many machine learning models have been developed in recent years to automate the histopathological classification of the different types of carcinomas. However, many of them are not scalable to large-scale datasets.