Skin Cancer Prediction Using Machine Learning Algorithms

2021 ◽  
pp. 303-310
Author(s):  
Arun Raj Lakshminarayanan ◽  
R. Bhuvaneshwari ◽  
S. Bhuvaneshwari ◽  
Saravanan Parthasarathy ◽  
Selvaprabu Jeganathan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Skin Cancer ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Cancer Prediction

scholarly journals Comparative Study of Machine Learning Algorithms for Breast Cancer Prediction - A Review

2019 ◽  
pp. 979-985
Author(s):  
Akshya Yadav ◽  
Imlikumla Jamir ◽  
Raj Rajeshwari Jain ◽  
Mayank Sohani
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Random Forest ◽  
Learning Algorithms ◽  
Accurate Diagnosis ◽  
Machine Learning Algorithms ◽  
Bayes Classifier ◽  
Cancer Prediction ◽  
Short Span ◽  
Cancerous Cells

Cancer has been characterized as one of the leading diseases that causes death in humans. Breast cancer being a subtype of cancer causes death in one out of every eight women worldwide. The solution to counter this is by conducting early and accurate diagnosis for faster treatment. To achieve such accuracy in a short span of time proves difficult with existing techniques. In this paper, different machine learning algorithms which can be used as tools by physicians for early and effective detection and prediction of cancerous cells have been studied and introduced. The different algorithms introduced here are ANN, DT, Random Forest (RF), Naive Bayes Classifier (NBC), SVM and KNN. These algorithms are trained with a dataset that contain parameters describing the tumor of a person having breast cancer and are then used to classify and predict whether the cell is cancerous.

scholarly journals Haar Wavelet Pyramid-Based Melanoma Skin Cancer Identification With Ensemble of Machine Learning Algorithms

2021 ◽  
Vol 16 (4) ◽  
pp. 1-15
Author(s):  
Sudeep D. Thepade ◽  
Gaurav Ramnani
Keyword(s):  
Machine Learning ◽  
Skin Cancer ◽  
Health Informatics ◽  
Performance Metrics ◽  
Learning Algorithms ◽  
Haar Wavelet ◽  
Machine Learning Algorithms ◽  
Computer Assisted ◽  
Marginal Improvement ◽  
Wavelet Pyramid

Melanoma is a mortal type of skin cancer. Early detection of melanoma significantly improves the patient’s chances of survival. Detection of melanoma at an early juncture demands expert doctors. The scarcity of such expert doctors is a major issue with healthcare systems globally. Computer-assisted diagnostics may prove helpful in this case. This paper proposes a health informatics system for melanoma identification using machine learning with dermoscopy skin images. In the proposed method, the features of dermoscopy skin images are extracted using the Haar wavelet pyramid various levels. These features are employed to train machine learning algorithms and ensembles for melanoma identification. The consideration of higher levels of Haar Wavelet Pyramid helps speed up the identification process. It is observed that the performance gradually improves from the Haar wavelet pyramid level 4x4 to 16x16, and shows marginal improvement further. The ensembles of machine learning algorithms have shown a boost in performance metrics compared to the use of individual machine learning algorithms.

Comparison of Machine Learning Algorithms in Breast Cancer Prediction Using the Coimbra Dataset

2019 ◽  
Author(s):  
Yolanda D Austria ◽  
Marie Luvett Goh ◽  
Lorenzo Sta. Maria Jr. ◽  
Jay-Ar Lalata ◽  
Joselito Eduard Goh ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Cancer Prediction

scholarly journals Machine Learning Algorithms For Breast Cancer Prediction And Diagnosis

2021 ◽  
Vol 191 ◽  
pp. 487-492
Author(s):  
Mohammed Amine Naji ◽  
Sanaa El Filali ◽  
Kawtar Aarika ◽  
EL Habib Benlahmar ◽  
Rachida Ait Abdelouhahid ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Cancer Prediction
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