Morsi, Yos S, Shi, Pujiang, Owida, Amal Ahmed, Hassan, Rafiul and Begg, Rezaul (2011) Breast Cancer: Advancement in Diagnostic and Treatment. In: Biomedical Engineering and Information Systems: Technologies, Tools and Applications. Shukla, Anupam and Tiwari, Ritu, eds. Medical Information Science Reference, Hershey, Pa, pp. 177-186.

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 disease 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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