Online ISSN: 2515-8260

Keywords : Sickle cell anemia


INTEGRATION OF MULTI-MODAL FEATURES FOR SICKLE CELL ANEMIA IDENTIFICATION USING MULTILAYER PERCEPTRON

G. Sridevi; V. Shanthi; J. Josphin Mary; R. Charanya

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 1407-1412
DOI: 10.31838/ejmcm.07.09.146

SCA is a legacy community of diseases of red blood cells. Persons with sickle cells in their red blood cells have abnormal protein. Sickle cell anemia is a red cell condition that is inherited and does not produce enough rotary cells in the body to hold oxygen. It may cause severe pain, anaemia and other symptoms. It is dangerous. The early diagnosis is required for sickle cell anemia. In this study, the integration of multi-modal features for sickle cell anemia identification using multilayer perceptron of SCA system is discussed. Initially, the input images are given to multimodel feature is used for feature extraction and Multilayer Perceptron (MP) classifier is used for classification. The performance of SCA system produces the classification accuracy of 95%using MP classifier.

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
DOI: 10.31838/ejmcm.07.09.165

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.

TO DETECT HEMOGLOBINOPATHIES BY DOING HEMOGLOBIN ELECTROPHORESIS IN MICROCYTIC HYPOCHROMIC ANEMIA

Ruqqaiya Bee; Alok Kumar Srivastav

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 3299-3310

The aim of the study was analyze the types of haemoglobinopathies in patients of Anemia using hemoglobin electrophoresis. Haemoglobinopathies like thalassaemia and sickle cell anemia etc are increasing due to unawareness of rural population. Microcytic hypochromic anemia is common problem in central India. The haemoglobinopathies (Structural and functional disorders of haemoglobin) are major World health problem. These are single gene,autosomal,recessive monogenic disorders that include thalassaemia and sickle cell anemia. Hemoglobinopathies presents as microcytic hypochromic anemia.They are misdiagnosed and treated as iron deficiency anemiainhemoglobinopathies iron is not required by the body. This causes burden to the patient economically as well as on health. The excess iron which is not required by body has a toxic effect on the body. By
doing electrophoresis in microcytic hypochromic anemia, we can categorize anemia into different groups. Electrophoresis helps in giving correct diagnosis. Most common cause of microcytic hypochromic anemia was iron deficiency anemia and abnormal hemoglobin disorder . Differential diagnosis based on complete hemogram and peripheral smear is possible but special tests like serum iron profile and haemoglobin electrophoresis are a must for confirmation of the diagnosis.