Filters








10,594 Hits in 4.6 sec

Artificial neural networks in urology: Update 2000

T Reckwitz, SR Potter, PB Snow, Z Zhang, RW Veltri, AW Partin
1999 Prostate Cancer and Prostatic Diseases  
This review focuses on recently developed neural networks for detecting, staging and monitoring prostate cancer.  ...  Arti®cial neural networks (ANNs) are widely available and have been demonstrated to be superior to standard empirical methods of detecting, staging and monitoring prostate cancer.  ...  Tewari and Narayan 10 subsequently performed a larger study assessing the usefulness of neural networks for pretreatment staging of prostate cancer patients.  ... 
doi:10.1038/sj.pcan.4500374 pmid:12497167 fatcat:xcm2qm4pvbgs7cbqbrehawn54y

Artificial neural networks for decision-making in urologic oncology

Theodore Anagnostou, Mesut Remzi, Bob Djavan
2003 Reviews in urology  
The use of ANNs in prostate cancer is ideal because of 1) multiple predicting factors that influence outcome; 2) the desire to offer individual consulting based on various tests; 3) the fact that prior  ...  Artificial neural networks (ANNs) are computational methodologies that perform multifactorial analyses, inspired by networks of biological neurons.  ...  [Rev Urol. 2003;5(1):15–21] © 2003 MedReviews, LLC Key words: Artificial neural networksProstate cancerProstate-specific antigen • Prostate biopsy • Prostate rebiopsy • Prostate cancer staging •  ... 
pmid:16985612 pmcid:PMC1472995 fatcat:6sqkb4xm45fxfi3szbbz2am72u

Pre-Operative Prediction of Advanced Prostatic Cancer Using Clinical Decision Support Systems: Accuracy Comparison between Support Vector Machine and Artificial Neural Network

Sang Youn Kim, Sung Kyoung Moon, Dae Chul Jung, Sung Il Hwang, Chang Kyu Sung, Jeong Yeon Cho, Seung Hyup Kim, Jiwon Lee, Hak Jong Lee
2011 Korean Journal of Radiology  
Objective: The purpose of the current study was to develop support vector machine (SVM) and artificial neural network (ANN) models for the pre-operative prediction of advanced prostate cancer by using  ...  biopsy parameters) and output data (the probability for advanced prostate cancer [> pT3a]).  ...  Support Systems based on logistic regression analysis and an artificial neural network (ANN) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) .  ... 
doi:10.3348/kjr.2011.12.5.588 pmid:21927560 pmcid:PMC3168800 fatcat:wzmgxwjjyvh4dkp3zzfomg2xs4

Prediction and Survival Rate Prostate Cancer Patient using Artificial Neural Network

Sameer Dixit, Shraddha Srivastava, Kamalesh Chandra
2017 International Journal of Computer Applications  
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  ...  PSPCPANN Project Overview The idea is to build model to improve prostate cancer detection and staging system.  ... 
doi:10.5120/ijca2017915940 fatcat:iyfcpogpbbdplevv5z2f32u7ci

A survey on computational intelligence approaches for predictive modeling in prostate cancer

Georgina Cosma, David Brown, Matthew Archer, Masood Khan, A. Graham Pockley
2017 Expert systems with applications  
Networks, Deep Learning, Fuzzy based approaches, and hybrids of these, as well as Bayesian based approaches, and Markov models.  ...  cancer predictive models, and the suitability of these approaches are discussed.  ...  Neural networks are also effective for early diagnosis of prostate cancer when integrated into expert systems.  ... 
doi:10.1016/j.eswa.2016.11.006 fatcat:ii6gbq6qcbai5kxvcy4l7kkg54

Classification of Prostate Cancer and Determination of Related Factors with Different Artificial Neural Network

İ̇̇pek BALIKÇI ÇİÇEK, Zeynep TUNÇ
2020 MIDDLE BLACK SEA JOURNAL OF HEALTH SCIENCE  
Network (MLPNN) and Radial-Based Function Neural Network (RBFNN) methods on the open access Prostate cancer dataset.  ...  To classify prostate cancer, MLPNN and RBFNN methods, which are artificial neural network models, is used.  ...  In this study, multilayer artificial neural network and radial-based artificial neural network models, which are among the artificial neural network models, were applied on an open access prostate cancer  ... 
doi:10.19127/mbsjohs.798559 fatcat:ocphhguj2jaqjhn6kpkdzyr63u

Artificial Neural Networks for Decision-Making in Urologic Oncology

Theodore Anagnostou, Mesut Remzi, Michael Lykourinas, Bob Djavan
2003 European Urology  
The authors are presenting a thorough introduction in Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology.  ...  The data are from real patients and reflect attempts to achieve more accurate diagnosis and prognosis, especially in prostate cancer that stands as a good example of difficult decision-making in everyday  ...  [40] are currently the most widely used and accepted mod-els for predicting pathological stage of the disease in cases of localized prostate cancer.  ... 
doi:10.1016/s0302-2838(03)00133-7 pmid:12767358 fatcat:yvy2khfojbfudfyiiwtwsvctxi

An Intelligent Decision-Making Support System for the Detection and Staging of Prostate Cancer in Developing Countries

Jun Zhang, Zhigang Chen, Jia Wu, Kanghuai Liu
2020 Computational and Mathematical Methods in Medicine  
In this study, a new data decision-making intelligent system for prostate cancer based on perceptron neural network is proposed, which mainly makes decisions by associating some relevant disease indicators  ...  Through the study of hospitalization information of more than 8,000 prostate patients in three hospitals, about 2,156,528 data items were collected and compiled for experiment purposes.  ...  Neural Network Model of Machine-Aided Diagnosis System for Prostate Cancer under Big Data Environment.  ... 
doi:10.1155/2020/5363549 pmid:32879636 pmcid:PMC7448109 fatcat:dt6vtdhx75cy7g4nupbk3vvl6e

Development of Integrated Data and Prediction System Platform for the Localized Prostate Cancer

Sun Jung Lee, Sung Hye Yu, Yejin Kim, Jun Hyuk Hong, Choung-Soo Kim, Seong Il Seo, Chang Wook Jeong, Seok-Soo Byun, Byung Ha Chung, Ji Youl Lee, In Young Choi
2019 Studies in Health Technology and Informatics  
In this study, we built a multi-center integrated database platform of localized prostate cancer and developed biochemical recurrence (BCR) prediction system with Gradient Boosted Regression model using  ...  Korean Prostate Cancer Registry (KPCR) database.  ...  Conclusions In this study, we designed a management system platform for Korean prostate cancer patients.  ... 
doi:10.3233/shti190507 pmid:31438204 fatcat:6hujhbdqnfhtvjxxxfmhwton54

Development of a Computerised Prostate Cancer Detection System using Artificial Neural Network

2019 International journal of recent technology and engineering  
The purpose of this research paper is to use an artificial neural network to predict the occurrence of prostate cancer in men.  ...  The proposed system can then predict whether there is possibility of prostate cancer from the parameters entered.  ...  In this paper work, a desktop based medical expert system using artificial neural network for standardized prediction has been developed and implemented to forecast the traces of prostate cancer in a patient  ... 
doi:10.35940/ijrte.c4486.098319 fatcat:cijuin6h25g2npp7xng7qcgole

A Review on Prostate Cancer Detection using CNN

Merlyn Koonamparampath, Raj Shah, Mahipal Sundvesha, Meena Ugale
2022 International Journal for Research in Applied Science and Engineering Technology  
Keywords: Convolutional Neural Network, Deep Learning, Prostate Cancer Detection, Artificial Intelligence, Survey.  ...  We've noticed that the use of CNN has skyrocketed, with outstanding results obtained either with fresh models or employing pre-trained networks for transfer learning.  ...  s [6] CNN-based model for prostate segmentation in MRI. The network was first trained to predict cancer and added modules for predicting the parameters of the shape model.  ... 
doi:10.22214/ijraset.2022.40747 fatcat:inl6l6uaofcevinxyzlyilvbjm

Early prostate cancer diagnosis by using artificial neural networks and support vector machines

Murat Çınar, Mehmet Engin, Erkan Zeki Engin, Y. Ziya Ateşçi
2009 Expert systems with applications  
networks (ANN) and linear, polynomial, and radial based kernel functions of support vector machine (SVM).  ...  The aim of this study is to design a classifier based expert system for early diagnosis of the organ in constraint phase to reach informed decision making without biopsy by using some selected features  ...  Poulakis et al. (2004) developed and tested an artificial neural network (ANN) for predicting biochemical recurrence based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate-specific  ... 
doi:10.1016/j.eswa.2008.08.010 fatcat:3kwoncs53bcjpaspspvx6uumzy

Early Detection and Diagnosis of Prostate Cancer using Artificial Intelligence Concept

Onuiri Ernest, Awodele Oludele, Ebiesuwa Oluwaseun
2016 International Journal of Computer Applications  
The occurrence of this FPTR can be reduced by employing Artificial Intelligence (AI) techniques such as Artificial Neural Network (ANN) in evaluating the need for a patient to undergo biopsy.  ...  Current methods of screening for prostate cancer carried out through blood PSA tests (presence of high Prostate Specific Antigen in the blood) and digital rectal examinations due to their morphological  ...  for Predicting Pathological Stage of Clinically Localized Prostate Cancer in a Taiwanese Population An ANN model was developed to predict prostate cancer staging in patient prior to when they received  ... 
doi:10.5120/ijca2016911433 fatcat:h26tzt3f7be3lgdhct7hqmctdm

Genetic Adaptive Neural Network to Predict Biochemical Failure After Radical Prostatectomy: A Multi-institutional Study

Ashutosh Tewari, Mutta Issa, Rizk El-Galley, Hans Stricker, James Peabody, Julio Pow-Sang, Asim Shukla, Zev Wajsman, Mark Rubin, John Wei, James Montie, Raymond Demers (+9 others)
2001 Molecular urology  
Demographic data such as age, race, preoperative PSA, systemic biopsy based staging and Gleason scores were used to construct a neural network model.  ...  We have utilized preoperative parameters through a computer based genetic adaptive neural network model to predict recurrence in such patients, which can help primary care physicians and urologists in  ...  [15] [16] [17] [18] [19] [20] [21] [22] Recently, artificial intelligence-based neural networks (ANNs) have become available for medical predictions.  ... 
doi:10.1089/10915360152745849 pmid:11790278 fatcat:kxm572mh2jfrpl7m3nyradjei4

Neural network analysis of combined conventional and experimental prognostic markers in prostate cancer: a pilot study

RN Naguib, MC Robinson, DE Neal, FC Hamdy
1998 British Journal of Cancer  
The aim of this study was to assess the value of artificial neural networks in predicting outcome in prostate cancer in comparison with statistical methods, using a combination of conventional and experimental  ...  This study was able to demonstrate the value of artificial neural networks in the analysis of prognostic markers in prostate cancer.  ...  Artificial neural networks Artificial neural networks (ANNs) are parallel informationprocessing structures that attempt to emulate certain performance characteristics of the biological neural system (  ... 
doi:10.1038/bjc.1998.472 pmid:9683301 pmcid:PMC2062883 fatcat:pjhch4g7rncgjk2wzi3etsxiky
« Previous Showing results 1 — 15 out of 10,594 results