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A Hybrid Deep Learning and Machine Learning Technique to Predict Ovarian Cancer

Principal Investigator
Name
Ahmad Ahmad
Degrees
B.Sc.
Institution
International Islamic University Chittagong
Position Title
Assistant Lecturer
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-976
Initial CDAS Request Approval
May 9, 2022
Title
A Hybrid Deep Learning and Machine Learning Technique to Predict Ovarian Cancer
Summary
Ovarian cancer (OC) is one of the most common types of cancer in women. It has been the world's largest seventh leading cause of death and disability in women. Therefore an accurate and early detection of ovarian cancer may beneficial for this deadly disease This project focuses on predicting ovarian cancer using machine learning and deep learning techniques for the early detection of ovarian cancer. Previous studies focused on predicting ovarian cancer from ovarian cysts using only machine learning. Our goal is to combine machine learning and deep learning techniques to predict ovarian cancer more accurately.
Aims

* Predict ovarian cancer from cysts using hybrid deep learning and machine learning technique.

Collaborators

Mohammad Arfizurrahman, International Islamic University Chittagong
Mohammad Shahadat Hossain, University of Chittagong