DocumentCode :
3090850
Title :
Hybrid intelligent systems in survival prediction of breast cancer
Author :
Ali, Ahmad ; Shamsuddin, Siti Mariyam ; Ralescu, Anca L.
Author_Institution :
Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear :
2012
fDate :
4-7 Dec. 2012
Firstpage :
555
Lastpage :
559
Abstract :
Hybrid intelligent systems play an important role in the survival prediction of breast cancer. The life-expectancy prediction of a patient is highly significant in decision making for treatments, medications and therapies. This paper addresses the motivation behind the need of hybrid model approach to survival prediction for breast cancer. The conventional approach of survival prediction faces difficulties in handling complex non-linear correlation between the prognostic factors and tumor progression, the censoring issue in medical data and the need to process the growing number of macro-scale and molecular-scale prognostic factors. The issues in breast cancer survivability are discussed with some examples of prominent works from machine learning approaches. Current trends and advancements of hybrid intelligent system are also presented.
Keywords :
cancer; decision making; gynaecology; learning (artificial intelligence); medical computing; patient treatment; tumours; breast cancer; decision making; hybrid intelligent systems; life-expectancy prediction; machine learning approaches; macro-scale prognostic factors; medications; molecular-scale prognostic factors; nonlinear correlation; survival prediction; therapies; treatments; tumor progression; Cancer; Medical diagnostic imaging; USA Councils; hybrid model; machine learning; medical data; survival prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems (HIS), 2012 12th International Conference on
Conference_Location :
Pune
Print_ISBN :
978-1-4673-5114-0
Type :
conf
DOI :
10.1109/HIS.2012.6421394
Filename :
6421394
Link To Document :
بازگشت