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Breast Cancer: Advancement in Diagnostic and Treatment

Breast Cancer: Advancement in Diagnostic and Treatment
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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

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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.

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