Ovarian Cancer Classification
To identify an efficient machine learning models on a comprehensive dataset including blood samples, general chemistry medical tests, and bio markers.
We have to develop a machine learning model using clinical data for the early diagnosis of ovarian cancer. Our model ensemble consists of various machine learning algorithms, including Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting Machine (XGBoost), Logistic Regression (LR), and Convolutional Neural Network (CNN). These models were trained to classify patients into benign and malignant ovarian cancer categories.
Puducherry Technological University