Use of Deep Learning Approaches in Cancer Diagnosis


Calp M. H.

in: Deep Learning for Cancer Diagnosis, Utku Kose,Jafar Alzubi, Editor, Springer, London/Berlin , Singapore, pp.249-267, 2021

  • Publication Type: Book Chapter / Chapter Research Book
  • Publication Date: 2021
  • Publisher: Springer, London/Berlin 
  • City: Singapore
  • Page Numbers: pp.249-267
  • Editors: Utku Kose,Jafar Alzubi, Editor

Abstract

Cancer is among serious health problems with an uncertain and complex

structure that causes fatal results. Cancer is a disease that consists of uncontrolled

proliferation of cells in different organs, whose clinical appearance, treatment and

approach are different from each other and that should be controlled in the early

stages. The cancer burden should be estimated in order to determine priorities for

cancer control. In this context, there are many studies on diagnosis and treatment

methods and a rapid development is observed in this regard. The aim is to increase

the survival rate of people with cancer. In order to achieve this goal effectively,

early and accurate diagnosis is especially important in the treatment of cancer, as

it causes fatal results. It is known that cancer is very difficult to diagnose in the

early stages and accurately with traditional diagnostic methods. At this point, the

artificial intelligence, a new or current approach, comes to the agenda. Developments

in this area offer very important opportunities in cancer diagnosis as in many areas.

Therefore, in this study, deep learning approaches which are an artificial intelligence

technique in the literature for the diagnosis of cancer disease are examined, and the

applications in the literature on how these approaches are used are included. Since

the subject of the study is up to date, it is considered that the study will be a guide

for people or institutions working in this field.