Superior Machine Learning Method for breast cancer cell lines identification
Author:
Affiliation:
1. Instituto de Pesquisas Energéticas e Nucleares (IPEN),Center for Lasers and Applications(CLA),Sao Paulo,Brazil
2. Instituto de Pesquisas Energéticas e Nucleares (IPEN),Center for Radiopharmaceutics,Sao Paulo,Brazil
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9992291/9992351/09992467.pdf?arnumber=9992467
Reference7 articles.
1. The impact of scan number and its preprocessing in micro-FTIR imaging when applying machine learning for breast cancer subtypes classification
2. Breast Cancer Consensus Subtypes: A system for subtyping breast cancer tumors based on gene expression
3. Breast Cancer Cell Line Classification and Its Relevance with Breast Tumor Subtyping
4. Neighbourhood components analysis;goldberger;Advances in neural information processing systems,2004
5. Breast Cancer Consensus Subtypes: A system for subtyping breast cancer tumors based on gene expression
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1. Dynamic light scattering microscopy sensing mitochondria dynamics for label-free detection of triple-negative breast cancer enhanced by deep learning;Biomedical Optics Express;2023-09-06
2. Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods;Applied Optics;2023-02-08
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