Publication Type : Conference Proceedings
Publisher : Springer Nature Singapore
Source : Lecture Notes in Networks and Systems
Url : https://doi.org/10.1007/978-981-19-9858-4_9
Campus : Bengaluru
School : School of Artificial Intelligence
Year : 2023
Abstract : This research developed an expert system based on the neural network to analyze prostate cancer risk. This model does not diagnose prostate cancer but helps a medical practitioner avoid unnecessary biopsies. An artificial neural network is created using the data from 119 patients with four attributes of prostate cancer (PSA, % free PSA, prostate volume, and age) as input parameters, and biopsy results are used as outputs. Outputs are divided into two classes positive and negative. The 70% data is used for training the network, and 30% is used for validation and testing. The results are demonstrated by confusion matrix and ROC curve. The suggested approach yielded an accuracy of 72.2%, which is higher than other existing methods.
Cite this Research Publication : Anjali Patel, Subhankar Jana, Juthika Mahanta, Prostate Cancer Risk Analysis Using Artificial Neural Network, Lecture Notes in Networks and Systems, Springer Nature Singapore, 2023, https://doi.org/10.1007/978-981-19-9858-4_9