Breast Cancer Prediction Using Artificial Intelligence Technology
Venkatraman Akila, J. Anita Christaline · 2024
The aim of the project is to compare the performance of four different machine learning algorithms for breast cancer prediction such as decision tree, logistic regression, XG boost, and CAT boost. We used a dataset of patient medical records containing various clinical factors to train and test the algorithms. Accurate diagnosis and early detection are essential for enhancing patient outcomes. Data mining is a prominent tool in the healthcare industry for processing massive amounts of data. To examine massive amounts of complicated medical data, researchers use a variety of data mining and machine learning approaches. The use of these strategies can help medical practitioners forecast the onset of breast cancer.