Review of Machine Learning Techniques in Anemia Recognition

Jameela Ali Akrimi, Abdul Rahim Ahmad, Loay E. George

Abstract: Machine learning procedure offers a major platform in cases where a model lacks and the amount of data is enormous in explaining the relation and the generation of the data that is set. A research on trends and application of machine learning such as algorithms, techniques, and methods present practical functions for problem solving and application of techniques in settling and automatic data extraction. Anemia is one of the common diseases affecting individuals worldwide. In this study, due to lack of a distinct models, an artificial neural network (ANN) and support vector machines (SVM) have been put in place to establish a non linear function that is continuous and expresses the interdependency of the data collected and erythrocytes levels. 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 anemic conditions.

Keywords: Artificial neural networks, support vector machines, statistical models

How to Cite?: Jameela Ali Akrimi, Abdul Rahim Ahmad, Loay E. George, "Review of Machine Learning Techniques in Anemia Recognition", Volume 2 Issue 3, March 2013, International Journal of Science and Research (IJSR), Pages: 140-142, https://www.ijsr.net/getabstract.php?paperid=IJSRON2013370, DOI: https://dx.doi.org/10.21275/IJSRON2013370