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  2. Volume 7, Issue 9
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Online ISSN: 2515-8260

Volume7, Issue9

AUTOMATIC CLASSIFICATION OF SICKLE CELL ANEMIA USING RANDOM FOREST CLASSIFIER

    S. Ranjana R. Manimegala K. Priya

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 1530-1534
10.31838/ejmcm.07.09.165

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Abstract

SCA is a genetic category of red diseases of the blood cells. People in their red blood cells contain an abnormal protein. Part of a group of SCA diseases is sickle cell anaemia (SCA). Sickle cell anaemia is a red blood cell condition that has not been inherited in the body with ample red cells to hold oxygen.. It is dangerous because it can cause extreme pain, anemia and other symptoms. The early diagnosis is required for sickle cell anemia. In this study, the automatic classification of SCA system is discussed. Initially, the input images are given to median filter for pre-processing. Then the Gray Level Co-occurrence Matrix (GLCM) and Haralick features are extracted. Finally, Random Forest (RF) classifier is used for Prediction. The performance of SCA system produces the classification accuracy of 95%using RF classifier.
Keywords:
    Sickle cell anemia Gray level co-occurrence matrix haralick features Random Forest
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(2020). AUTOMATIC CLASSIFICATION OF SICKLE CELL ANEMIA USING RANDOM FOREST CLASSIFIER. European Journal of Molecular & Clinical Medicine, 7(9), 1530-1534. doi: 10.31838/ejmcm.07.09.165
S. Ranjana; R. Manimegala; K. Priya. "AUTOMATIC CLASSIFICATION OF SICKLE CELL ANEMIA USING RANDOM FOREST CLASSIFIER". European Journal of Molecular & Clinical Medicine, 7, 9, 2020, 1530-1534. doi: 10.31838/ejmcm.07.09.165
(2020). 'AUTOMATIC CLASSIFICATION OF SICKLE CELL ANEMIA USING RANDOM FOREST CLASSIFIER', European Journal of Molecular & Clinical Medicine, 7(9), pp. 1530-1534. doi: 10.31838/ejmcm.07.09.165
AUTOMATIC CLASSIFICATION OF SICKLE CELL ANEMIA USING RANDOM FOREST CLASSIFIER. European Journal of Molecular & Clinical Medicine, 2020; 7(9): 1530-1534. doi: 10.31838/ejmcm.07.09.165
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