scholarly journals Machine Learning Classifiers on Breast Cancer Recurrences

2021 ◽  
Vol 192 ◽  
pp. 2742-2752
Author(s):  
Vincent Peter C. Magboo ◽  
Ma. Sheila A. Magboo
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Machine Learning Classifiers ◽  
Learning Classifiers

scholarly journals Prediction of survival and metastasis in breast cancer patients using machine learning classifiers

2019 ◽  
Vol 7 (3) ◽  
pp. 293-299 ◽  
Author(s):  
Leili Tapak ◽  
Nasrin Shirmohammadi-Khorram ◽  
Payam Amini ◽  
Behnaz Alafchi ◽  
Omid Hamidi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Prediction Of Survival

An Analysis of Machine Learning Classifiers in Breast Cancer Diagnosis

2019 ◽  
Author(s):  
Fabiano Teixeira ◽  
Joao Luis Zeni Montenegro ◽  
Cristiano Andre da Costa ◽  
Rodrigo da Rosa Righi
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Machine Learning Classifiers ◽  
Learning Classifiers

Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis

2011 ◽  
Vol 36 (4) ◽  
pp. 2259-2269 ◽  
Author(s):  
Raúl Ramos-Pollán ◽  
Miguel Angel Guevara-López ◽  
Cesar Suárez-Ortega ◽  
Guillermo Díaz-Herrero ◽  
Jose Miguel Franco-Valiente ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Machine Learning Classifiers ◽  
Learning Classifiers

THE EFFECT OF DATASETS ON BREAST CANCER DETECTION MODELS

2021 ◽  
Vol 4 (4) ◽  
pp. 309-315
Author(s):  
Kumawuese Jennifer Kurugh ◽  
Muhammad Aminu Ahmad ◽  
Awwal Ahmad Babajo
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Learning Algorithms ◽  
Cancer Classification ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Breast Cancer Dataset ◽  
Machine Learning Classifiers ◽  
Breast Cancer Classification ◽  
Learning Classifiers

Datasets are a major requirement in the development of breast cancer classification/detection models using machine learning algorithms. These models can provide an effective, accurate and less expensive diagnosis method and reduce life losses. However, using the same machine learning algorithms on different datasets yields different results. This research developed several machine learning models for breast cancer classification/detection using Random forest, support vector machine, K Nearest Neighbors, Gaussian Naïve Bayes, Perceptron and Logistic regression. Three widely used test data sets were used; Wisconsin Breast Cancer (WBC) Original, Wisconsin Diagnostic Breast Cancer (WDBC) and Wisconsin Prognostic Breast Cancer (WPBC). The results show that datasets affect the performance of machine learning classifiers. Also, the machine learning classifiers have different performances with a given breast cancer dataset

scholarly journals Prediction of Attendance to the "Law of 60 Days" in Breast Cancer Patients using Machine Learning Classifiers

2020 ◽  
Vol 4 (3) ◽  
pp. 01-11
Author(s):  
Sandra Gioia ◽  
Renata Galdino ◽  
Lucia Brigagão ◽  
Antonio Valadares ◽  
Fernando Secol ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
The Law
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