@Article{Świetlik2007,
journal="Contemporary Oncology/Współczesna Onkologia",
issn="1428-2526",
volume="11",
number="8",
year="2007",
title="An application of artificial neural networks in breast cancer recognition using scintimammography",
abstract="The aim of the study was to assess the usefulness of artificial neural networks (ANN) application in evaluation of  scintimammography in the context of clinical data in the diagnosis of breast cancer. The results produced by ANN were compared with the diagnosis of two independent observers, nuclear medicine specialists. Material and methods: The clinical data and the numerical values derived from scintimammograms of 103 patients were the material for the study. The reference method was the result of histopathology study (core biopsy and /or FNB).  Results: The overall sensitivity of physician diagnosis was 78% with specificity of 72%. The ANN produced 71% sensitivity and specificity of 73%. The physicians\’ and ANN results were not significantly different (p=0.4619). Conclusions: Artificial neutral networks are useful tool in clinical diagnosis of breast cancer.",
author="Świetlik, Dariusz
and Bandurski, Tomasz
and Masiuk, Mariusz",
pages="385--389",
url="https://www.termedia.pl/An-application-of-artificial-neural-networks-in-breast-cancer-recognition-using-scintimammography,3,9292,1,1.html"
}