Literature DB >> 9309779

Artificial neural networks in cancer research.

R N Naguib1, G V Sherbet.   

Abstract

The concept of artificial neural networks dates back to the early part of this century. However, their use in biological and medical research has only vastly proliferated during the last few years. It is now clear that these networks, which attempt to emulate functions of the human brain, can play a vital role in the field of cancer research, where they could be used in the diagnosis, prognosis and patient management stages of cancer evaluation. This paper presents a review of the underlying theory behind artificial neural networks and gives a broad overview of their many areas of application within the cancer field. This is achieved through the prognostic analysis of prostate cancer markers, the non-invasive diagnosis of lymph node involvement in breast cancer patients and the assessment of image cytometric data for predicting the metastatic potential of breast cancer.

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Year:  1997        PMID: 9309779     DOI: 10.1159/000164114

Source DB:  PubMed          Journal:  Pathobiology        ISSN: 1015-2008            Impact factor:   4.342


  2 in total

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

Authors:  R N Naguib; M C Robinson; D E Neal; F C Hamdy
Journal:  Br J Cancer       Date:  1998-07       Impact factor: 7.640

Review 2.  Non-muscle invasive bladder cancer risk stratification.

Authors:  Sumit Isharwal; Badrinath Konety
Journal:  Indian J Urol       Date:  2015 Oct-Dec
  2 in total

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