A New Prediction Model for Pathological Stages and Treatments for Patients with Prostate Cancer
Principal Investigator
Name
Alfadil Hamdan
Degrees
M.D
Institution
Sudan University
Position Title
Lecturer
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-377
Initial CDAS Request Approval
Jun 27, 2018
Title
A New Prediction Model for Pathological Stages and Treatments for Patients with Prostate Cancer
Summary
Prostate cancer is the most common cancer in men in many countries over the world, in the UK, with 47,700 new cases in 2015 (CRUK 2017) [1]. In USA, prostate cancer is the most common cancer after skin cancer. According to American cancer Society’s for prostate cancer in the United States in 2018, estimates that About 164,690 new cases of prostate cancer and 29,430 deaths from prostate cancer [2]. In Kenya, prostate cancer has been ranked the third as a cause of death after infectious and cardiovascular diseases [3]. Prostate cancer is among the top killing cancers.
Our model expected to help to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results.
Our model expected to help to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results.
Aims
• To review some of the previous related works on prostate cancer prediction and treatments.
• To propose an algorithm that:
1) Identify machine learning techniques appropriate for prostate cancer analysis.
2) Design a model for prostate cancer data analysis and prediction.
• To compare the proposed approach with the existing related algorithm that performs similar task.
Collaborators
Prof. Mohand Tahar Kechadi (PhD)