文章基本信息

标题：A Review of Breast Cancer Detection using ART Model of Neural Networks
本地全文：下载
作者：Sonia Narang ; Harsh K Verma ; Uday Sachdev 等
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：10
出版社：S.S. Mishra
摘要：Artificial neural networks have featured in a wide range of medical journals, often with promising results. This paper reports on a systematic review that was conducted to assess the benefit of artificial neural networks (ANNs) as decision making tools in the field of cancer. The number of clinical trials (CTs) and randomised controlled trials (RCTs) involving the use of ANNs in diagnosis and prognosis increased from 1 to 38 in the last decade. However, out of 396 studies involving the use of ANNs in cancer, only 27 were either CTs or RCTs. Neural Networks are currently a 'hot' research area in medicine, particularly in the fields of radiology, urology, cardiology, oncology and etc. The main aim of research in medical diagnostics is to develop more cost-effective and easy¨C to-use systems, procedures and methods for supporting clinicians. Breast cancer diagnosis has been approached by various machine learning techniques for many years. This paper presents a review on classification of Breast cancer using Adaptive Resonance Neural Networks (ARNN), ART, and Feed Forward Artificial Neural Networks. The performance of the network is evaluated using Wisconsin breast cancer data set for various training algorithms.
关键词：Artificial neural networks; Breast Cancer; ARNN; ART; Medical decision making