A machine learning based framework for assisting pathologists in grading and counting of breast cancer cells
Breast cancer normally occurs in the breast cells of both men and women, but is prominent in women. Computer aided detection increases the chance of early detection and diagnosis. This paper proposes a breast cancer detection method using Nuclear Atypia Scoring (NAS). The proposed cancer detection m...
Guardado en:
Autores principales: | Sreeraj M., Jestin Joy |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/6bc1ccd293a04bb1b5726d71ee40e4b4 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
An Intelligent Hierarchical Security Framework for VANETs
por: Fábio Gonçalves, et al.
Publicado: (2021) -
A Text Mining Approach in the Classification of Free-Text Cancer Pathology Reports from the South African National Health Laboratory Services
por: Okechinyere J. Achilonu, et al.
Publicado: (2021) -
ANALYSIS OF MACHINE LEARNING METHODS FOR PREDICTIONS OF STOCK EXCHANGE SHARE PRICES
por: V. Serbin, et al.
Publicado: (2021) -
Turning the blackbox into a glassbox: An explainable machine learning approach for understanding hospitality customer
por: Ritu Sharma, et al.
Publicado: (2021) -
Exploring the Impact of COVID-19 on Social Life by Deep Learning
por: Jose Antonio Jijon-Vorbeck, et al.
Publicado: (2021)