International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 5 Issue: 11 68 – 71 _______________________________________________________________________________________________ 68 IJRITCC | November 2017, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Prediction & Survival Rate Prostate Cancer Patient using Artificial Neural Network Er. Sameer Dixit 1 (Asst. Professor), Integral University, Lucknow,Email-samdixit007@gmail.com Shraddha Srivastava 2 .HBTI, Kanpur, Email-sharaddha0266@gmail.com Er. Amit Srivastava 3 , Integral University, Lucknow,Email-amitkr@iul.ac.in Abstract- Prostate cancer is that starts in the prostate gland. The prostate is a small, walnut sized structure that makes up part of a man’s reproductive system. It wraps around the urethra, the tube that carries urine out of the body. Prostate cancer is the most common cause of death from cancer in men over age 75. Prostate cancer is rarely found in men younger than 40.Current method of screening for prostate cancer carried out through blood test& presence of high PSA lead to a high percentage of false positive result which can be reduced by employing intelligent Artificial Neural Networks. The main aim of our research paper and the parallel undertaking of its practical implementation is to develop a mathematical model to improve prostate cancer detection and staging system and finally to present a deploy ready marketable solution based on the model which can be installed across various screening, centers,hospital and research organization. Keyword-PSA, ANN,MLP etc. __________________________________________________*****_________________________________________________ I. INTRODUCTION (1)Why is the emphasis on prostate cancer? American Cancer Society (ACS) estimates for 2005 include 232090 new cases of prostate cancer in the U.S.Year2005 estimates include 30350 deaths occurring from prostate cancer in the US alone, making it the second leading cause of cancer death in men. African-American men have about a 70 percent higher incidence rate of prostate cancer Caucasian men and nearly a two-higher mortality rate than Caucasian men. (2) The Need for efficient prostate cancer screening and diagnostic methods. Physicians are relying on the results from the PSA blood test to diagnose prostate cancer.Prostate-specific antigen (PSA) is a protein produced by cells of the prostate gland. The PSA test measures the level of PSA in the blood.The U.S. Food and Drug Administration (FDA) has approved the use of the PSA test along with a digital rectal exam to help detect prostate cancer in men age 50 and older. The FDA has also approved the PSA test to monitor patients with a history of prostate cancer to see if the cancer has recurred (come back)Doctors’ recommendations for PSA screening vary. The higher a man’s PSA level, the more likely it is that cancer is present, but there are other possible reasons for an elevated PSA level. Doctors take several factors into account for men who have a rising PSA level after treatment for prostate cancer. The PSA test for screening has limitations and is still controversial. Researchers are studying ways to validate and improve the PSA test and to find other ways of detecting prostate cancer early. Hence the goal of this paper is to employ Intelligent Artificial Neural Networks to build a deploy ready marketable mathematical model to reduce the non-required trial and error method and expedite early cancer diagnosis and treatment. II. PROJECT OVERVIEW The idea is to build model to improve prostate cancer detection and staging system. Here the basis is to add intelligence to Artificial Neural Networks and produce a deploy-ready mathematical model that revolves around the concept of ANN. The actual implementation of the model would require building a standalone software application which would be installed across screening centers, hospitals, and research institutions. Theproject is in its intermediate stage and the team is working on the development and implementation stage and to bring the product to the masses.C is the choice of programming language to be used for the reasons of its strong mathematical library and Matlab is used as the simulation software package to test our software runs. This research project is a long term initiative involving successive refinements to the first version of our model. Artificial Neural Network- An ANN is efficient information processing system which resembles in characteristics with a biological neural network. The biological neuron consists of three main parts. Soma or cell body – where the cell nucleus is located. Dendrites – where the nerve is connected to the cell body. Axon – This carries the impulses of the neuron.