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Computational Studies in Breast Cancer
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Author(s): Monika Lamba (The Northcap University, India), Geetika Munjal (Amity University, India)and Yogita Gigras (The Northcap University, India)
Copyright: 2021
Pages: 21
Source title:
Diagnostic Applications of Health Intelligence and Surveillance Systems
Source Author(s)/Editor(s): Divakar Yadav (National Institute of Technology, Hamirpur, India), Abhay Bansal (Amity University, India), Madhulika Bhatia (Amity University, India), Madhurima Hooda (Amity University, India)and Jorge Morato (Universidad Carlos III de Madrid, Spain)
DOI: 10.4018/978-1-7998-6527-8.ch005
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Abstract
Early detection of breast cancer is a worldwide need as many hospitals have appeared in commitment of research pathway. As per WHO (World Health Organisation), early detection of breast cancer boosts the choice of making corrective judgement on medication plan. This corrective choice helps women to save themselves from expensive and unwanted medical test and treatment. Physical observation and medical history play an important role in diagnosing this disease; however, for detailed understanding, some reliable and accurate methods are still required. This chapter reviews existing computational methods and need of novel algorithms that can help in accurately diagnosing this disease. Correct diagnosis and yield results devising treatment strategy. For correct diagnosis micro-array gene expression data is widely used, this chapter highlights various computational studies done on breast cancer microarray data. This review highlights the benefit of computational model being an impressive tool for discovery of cancer along with devising its therapies.
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