Superior Machine Learning Method for breast cancer cell lines identification

Author(s)

Farooq, Sajid ; Caramel-Juvino, Amanda ; Del-Valle, Matheus ; Santos, Sofia ; Bernandes, Emerson Soares ; Zezell, Denise Maria ; IEEE

• Document type: Journal article
• Source: 2022 SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE (SBFOTON IOPC); v. N/A, p. 3-pg., 2022-01-01.

Abstract

We propose an artificial intelligence platform based on machine learning (ML) algorithm using Neighborhood Component analysis and K-Nearest Neighbors for breast cancer cell lines recognition. Our model presents up to 97% accuracy for identification of breast cancer cell lines. (AU)

• FAPESP's process: 17/50332-0 - Scientific, technological and infrastructure qualification in radiopharmaceuticals, radiation and entrepreneurship for health purposes (PDIp)
• Grantee: Marcelo Linardi
• Support Opportunities: Research Grants - State Research Institutes Modernization Program