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Normalized Neural Networks for Breast Cancer Classification
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
Effat Univ, Saudi Arabia.
2020 (Engelska)Ingår i: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, CMBEBIH 2019, SPRINGER , 2020, Vol. 73, s. 519-524Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In almost all parts of the world, breast cancer is one of the major causes of death among women. But at the same time, it is one of the most curable cancers if it is diagnosed at early stage. This paper tries to find a model that diagnose and classify breast cancer with high accuracy and help to both patients and doctors in the future. Here we develop a model using Normalized Multi Layer Perceptron Neural Network to classify breast cancer with high accuracy. The results achieved is very good (accuracy is 99.27%). It is very promising result compared to previous researches where Artificial Neural Networks were used. As benchmark test, Breast Cancer Wisconsin (Original) was used.

Ort, förlag, år, upplaga, sidor
SPRINGER , 2020. Vol. 73, s. 519-524
Serie
IFMBE Proceedings, ISSN 1680-0737
Nyckelord [en]
Breast cancer diagnosis; Supervised learning; Normalized neural networks; Multi layer perceptron; Breast cancer Wisconsin
Nationell ämneskategori
Cancer och onkologi
Identifikatorer
URN: urn:nbn:se:liu:diva-161585DOI: 10.1007/978-3-030-17971-7_77ISI: 000491311000077ISBN: 978-3-030-17971-7 (digital)ISBN: 978-3-030-17970-0 (tryckt)OAI: oai:DiVA.org:liu-161585DiVA, id: diva2:1368243
Konferens
International Conference on Medical and Biological Engineering in Bosnia and Herzegovina (CMBEBIH)
Tillgänglig från: 2019-11-06 Skapad: 2019-11-06 Senast uppdaterad: 2019-11-06

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Alickovic, Emina
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