A molecule called hemoglobin is found in red blood cells that holds oxygen all over the body. Hemoglobin is elastic, round, and stable in a healthy human. This makes it possible to float across red blood cells. But the composition of hemoglobin is unhealthy if you have sickle cell disease. It refers to compact and bent red blood cells. The odd cells obstruct the flow of blood. It is dangerous and can result in severe discomfort, organ damage, heart strokes, and other symptoms. The human life expectancy can be shortened as well. The early identification of sickle calls will help people recognize signs that can assist antibiotics, supplements, blood transfusion, pain-relieving medications, and treatments etc. The manual assessment, diagnosis, and cell count are time consuming process and may result in misclassification and count since millions of red blood cells are in one spell. When utilizing data mining techniques such as the multilayer perceptron classifier algorithm, sickle cells can be effectively detected with high precision in the human body. The proposed approach tackles the limitations of manual research by implementing a powerful and efficient MLP (Multi-Layer Perceptron) classification algorithm that distinguishes Sickle Cell Anemia (SCA) into three classes: Normal (N), Sickle Cells(S) and Thalassemia (T) in red blood cells. This paper also presents the precision degree of the MLP classifier algorithm with other popular mining and machine learning algorithms on the dataset obtained from the Thalassemia and Sickle Cell Society (TSCS) located in Rajendra Nagar, Hyderabad, Telangana, India. Doi: 10.28991/esj-2021-01270 Full Text: PDF

Sickle cell is haematological disorder (haematology is a study of blood in health and diseases) which may lead to an organ damage, heart strokes and serious complications. It may also reduce human life span. Most of the sickle cells are observed in new born babies. At the start of sickle cells in human people though it’s a kind of feature in tribal people but it has spread over the world. Sickle cell Symptoms are observed in human beings as episodes of pains (crisis), Vision problems, swelling of hands and Feet. Sickle Cell Disease (SCD) can harm patient’s spleen (slightly pain at left Ribs). If one organ is affected in human body, then slowly it affects the entire body by spreading into Brain, Lungs, Heart, Liver, Kidneys, Joints, Eyes, Penis, Skin or Bone. This paper is aimed at presenting the complete details of the SCD with its properties, symptoms, signs, treatment for this disease. This is also a comprehensive study and characteristics of this disease with other similar diseases. The technological implications and usage in the field of SCD for better accuracy of identification of the disease is presented.

Chronic kidney disease (CKD) in children is a devastating illness, and the mortality rate of the children is high and majority of them present at the later stages of disease. Early diagnosis of renal diseases with effective preventive and interventional strategies will help in reducing the burden of the disease. Urine protein estimation is one of the simplest, least expensive method to detect urinary abnormalities which may suggest the presence of renal disease. Presence of proteins in urine is termed proteinuria and its presence for more than 3 occasions is termed persistent proteinuria(PP). The present study is a cross-sectional one and was planned to determine prevalence of persistent proteinuria in 500 healthy school children aged between 8-16 years. Out of 500 students, proteinuria was positive in 4.4% of the students in the first visit and persistent in 2.4%. Proteinuria was positive and persistent in 1.8% of girls and 0.6% of boys. Proteinuria is an early marker of kidney disease. It is important to identify these cases to detect renal disease if any so that remedial steps can be taken to prevent the associated morbidity. Children with persistent proteinuria should be subjected to follow-up and further workup to identify the cause.

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