Study
PLCO
(Learn more about this study)
Project ID
PLCO-314
Initial CDAS Request Approval
Oct 16, 2017
Title
Biopsy Recommendation in Prostate Cancer Using Machine Learning Techniques
Summary
We are starting our research titled "Biopsy Recommendation in Prostate Cancer Using Machine Learning Techniques" .The research aim to develop a machine learning model that will make reliable prediction based on provided classifier about if the person should go for biopsy or not. We also aim to make our model capable of differentiating between prostate cancer and B.P.H (Benign Prostatic Hyperplasia), that is to differentiate if the person is infected with cancer or the body is just going through some changes because of aging and that will be achieved using machine learning algorithms .The importance of the project is that it will save precious time that is otherwise wasted during the diagnosis phase and would also try to generate better results while being cost effective. This would also improve doctor’s confidence when referring a patient for biopsy as it will be a quick way of getting a second opinion. We are gathering data related to prostate cancer and access to related data will be a highly appreciated.
Aims
The ultimate objective of the project would be to find out classifiers that can efficiently differentiate between Prostate Cancer and B.P.H (Benign Prostatic Hyperplasia),and on the basis of that recommend if the patient should go for biopsy or not.As the treatment of both is significantly different, it would save all the hassle that the patients otherwise have to go through. This will not only be cost efficient as usually all patients go for second opinions but will also save time.
Collaborators
Project Supervisor :Muhammad Shahzad (mshahzad@nu.edu.pk), Assistant Professor, Department of Computer Science
Project Members :
Taha Tariq Khan (k142224@nu.edu.pk)
Umar Hanfi (k142806@nu.edu.pk)
Abdul Ahad Vayani (k142329@nu.edu.pk)
Shayan Arshi (k142244@nu.edu.pk)
Institute : FAST - National University of Computer and Emerging Sciences
