Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Identifying Breast Cancer Cell Lines Using High Performance Machine Learning Methods

Not Accessible

Your library or personal account may give you access

Abstract

We present a computational framework based on machine learning classifiers K-Nearest Neighbors and Neighborhood Component analysis for breast cancer (BC) subtypes prognostic. Our results has up to 97% accuracy for prognostic stratification of BC subtypes.

© 2022 The Author(s)

PDF Article
More Like This
Classifying Breast Cancer Cell Lines of Different Metastasis Potentials using Visible Resonance Raman Spectroscopy and Machine Learning

Binlin Wu, Lin Zhang, Kenneth Jimenez, Susie Boydston-White, Eric Wang, Cheng-hui Liu, and Robert R Alfano
AW2T.5 CLEO: Applications and Technology (CLEO:A&T) 2021

Breast Cancer Subtype Classification Using a One-Dimensional Convolutional Neural Network in Hyperspectral Images

Matheus del-Valle, Moises Oliveira dos Santos, Emerson Soares Bernardes, and Denise Maria Zezell
M4B.5 Latin America Optics and Photonics Conference (LAOP) 2022

Multi-Classification of Cell Lines using DHM and Machine Learning

Anyu Sun, Van Lam, Thuc Phan, Lin-Ching Chang, George Nehmetallah, and Christopher Raub
W5A.23 Digital Holography and Three-Dimensional Imaging (DH) 2022

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.