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Ovarian Cancer Classification

Principal Investigator

Name
Lakshmi kumari

Degrees
Ph.D

Institution
Puducherry Technological University

Position Title
Research scholar

Email
dsslakshmikumari@ptuniv.edu.in

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-1443

Initial CDAS Request Approval
Jan 16, 2024

Title
Ovarian Cancer Classification

Summary
In this direction, a methodology is designed to classify between Benign Ovarian and Tumor.
 To identify an efficient machine learning models on a comprehensive dataset including blood samples, general chemistry medical tests, and bio markers.

Aims

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.

Collaborators

Dr P.Maragathavalli,
Professor
Information Technology
Puducherry Technological University