A Review Of Machine Learning Techniques And Statistical Models In Anaemia
Journal: International Journal of Scientific & Technology Research (Vol.2, No. 2)Publication Date: 2013-02-25
Authors : Jameela Ali; AbdulRahim Ahmad; Loay E. George; Chen Soong Der; Sherna Aziz;
Page : 171-175
Keywords : Index Terms - Artificial neural networks; support vector machines; statistical models; Anaemic Red Blood Cell; cross validated;
Abstract
Abstract- Blood diseases have in the recent past become a major cause of mortality and morbidity all over the world. Consequently machine learning has emerged as one of the best and most fruitful methods of research in the present world both in terms of proposing of new techniques with effective theoretical algorithms and also in applying such methods in real life situations. From a technological view it is evident that there are major changes in the world that occur at an ever increasing pace. This has seen the development of systems which can be easily adapt to the environment in an effective way by being practically applicable. These systems work through optimizing performance using certain algorithm in accordance with its maximization or minimization criteria but also using experimental data instead of a given program. This study will identify the use of artificial neural networks support vector machines and statistical models and methods in the recognition of iron deficiency that leads to anaemic conditions.
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Last modified: 2013-04-13 21:56:02