IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Breast Cancer: Advancement in Diagnostic and Treatment

Breast Cancer: Advancement in Diagnostic and Treatment
View Sample PDF
Author(s): Yos S. Morsi (Swinburne University of Technology, Australia), Pujiang Shi (Swinburne University of Technology, Australia)and Amal Ahmed Owida (Swinburne University of Technology, Australia)
Copyright: 2011
Pages: 10
Source title: Biomedical Engineering and Information Systems: Technologies, Tools and Applications
Source Author(s)/Editor(s): Anupam Shukla (ABV – Indian Institute of Information, India)and Ritu Tiwari (ABV – Indian Institute of Information, India)
DOI: 10.4018/978-1-61692-004-3.ch009

Purchase

View Breast Cancer: Advancement in Diagnostic and Treatment on the publisher's website for pricing and purchasing information.

Abstract

Breast cancer is the second most common cancer in the world and is difficult to accurately identify and treat. Diagnostic computational tools can be used effectively, with high degree of accuracy, to recognize and differentiate between the two known types of breast lesion, namely benign and malignant. These modelling tools include artificial intelligence techniques such as Artificial Neural Networks (ANNs), Fuzzy Logic (FL), Hidden Markov Model (HMM) and Support Vector Machines (SVMs). These tools can identify the important features that play pivotal roles in the classification task, and can aid physicians to diagnose and prognosticate breast cancer. Moreover, recent advancement in nanotechnology indicates that with the aid of nanoparticles, nanowires, nanorobots and nanotubes, the disese of breast cancer can be potentially eradicated totally. The chapter highlights the limitations of the current therapies used in breast cancer and discusses the concept of nanotechnology as a possible future therapy.

Related Content

Saloua Mabsor-Zgandaoui, Khawla Rachmoune, Ilham Aftais, Fatima Ezzahra Elamrani, Imade Amradi, Adil El Housseini, Youssef Ait Hamdan, Youness Zgandaoui, Abdelghani Iddar, Mohammed El Mzibri, Adnane Moutaouakkil, Aboubaker El Hessni, Abdelhalim Mesfioui. © 2026. 30 pages.
Yusuf Olatunji Waidi. © 2026. 20 pages.
Ajinkya Nene, Sorour Sadeghzade, Wenjie Yang, Prakash Somani. © 2026. 12 pages.
Seyyed Mohammad Amin Mousavi-Sagharchi, Mahdieh Ranjbar-Jamalabadi, Sama Yavari, Elina Afrazeh, Naresh Poondla, Mohsen Sheykhhasan. © 2026. 32 pages.
Wenqiang Xie, Yuan Su, Ruiqi Zhang, Sijia Li, Jia Ni, Longquan Shao. © 2026. 18 pages.
Zhengao Wang, Huiyu Zhao, Yao Han, Wuyi Zhou, Chengyun Ning. © 2026. 30 pages.
Navya Aggarwal, Shinjini Sen, Tanmay J. Urs, Shreya Gupta, Banashree Bondhopadhyay. © 2026. 36 pages.
Body Bottom