… from complex BC datasets, machine learning (ML) is widely … and their applications in BC
diagnosis and prognosis. Firstly, … Our primary data is drawn from the Wisconsin breast cancer …

… Cancer is a complex and multifaced disorder with thousands of genetic … diagnosis, prognosis,
and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis …

… is the Wisconsin Diagnostic Breast Cancer Dataset (WDBC). The contribution of this research
is to show that machine learning approaches which include Support Vector Machine (SVM)…

… As many of these ML models are moving from lab to clinic, we also review the regulatory
process for approving ML methods for cancer diagnostics. We highlight examples of recently …

… image analysis methods with machine learning techniques. … , machine learning decisions
are usually dichotomous-- in our case, either benign or malignant. To acknowledge diagnostic …

… Machine learning techniques, such as microarray and next-generation sequencing … data;
various machine learning methods have been employed in cancer diagnostic research [48-50]. …

… of early diagnosis and prediction of cancer. In this paper, two of the most popular
machine learning techniques have been used for classification of Wisconsin Breast Cancer (Original) …

… data analysis techniques of machine learning and high-… After an introductory overview of
machine learning and … of these techniques to cancer detection, diagnosis, and management …

… classifiers of machine learning and deep learning approaches for breast cancer diagnosis.
… authors implementing diverse machine learning classifiers for diagnosing breast cancer. …

… cancer and reduce the death rate. This paper summarizes the survey on breast cancer diagnosis
using various machine learning … the accuracy of predicting cancer. This survey can also …