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Articles by A.A. Kayode
Total Records ( 2 ) for A.A. Kayode
  A.A. Kayode , N.O. Akande and E.O. Asani
  In the present day, the most rampant cancer discovered among women in various parts of the world is breast cancer. Early detection and diagnosis of breast cancer which can be achieved through mammography increases treatment options and a cure is more likely. In order to diagnose breast cancer, radiologists carefully examine patient’s X-ray images of the breast (mammograms) to see if there are significant visually extractable features that indicate the presence of breast cancer. However, visual features are subjective and diagnostic decisions should not be based on them because they are a function of radiologist’s opinion and experience. Thus, to eliminate the differential interpretations of abnormalities seen on mammograms among radiologists it is expedient to use computers to aid the extraction and selection of features which are not necessarily visually extractable. This study makes use of patient’s mammograms acquired from Radiology Department, Obafemi Awolowo University Teaching Hospital Complex Ile-Ife, Nigeria. Features are extracted from the mammograms using feature descriptors from Gray Level Co-occurrence Matrix (GLCM) and most discriminating features are selected using the proposed hybrid feature selection algorithm which is implemented to improve the classification accuracy. For each of the input image, the algorithm automatically selects relevant features from the set of extracted features. This algorithm reduces the extracted features by selecting the most relevant features thereby finding (near) optimal classification model of breast mammographic images. Two methods are combined for selecting optimal features viz.: the sequential forward selection and the Genetic algorithm. This is done, so as to cover the disadvantages of each one by the advantages of the other.
  O.T. Kayode , A.A. Kayode and A.A. Odetola
  Comparison was made between the efficacy of dietary protein replenishment and supplementation with Telfairia occidentalis leaves, in treatment of Protein Energy Malnutrition (PEM) induced liver damage. PEM rats were produced by feeding weanling rats a protein deficient diet (2% protein) for 28 days and then divided into four dietary treatment groups: 2% protein (group A; PEM control group); 20% protein and 10% T. occidentalis (group C); 20% protein (group D) and 10% T. occidentalis (group E). The protein deficient diet caused a significant increase (p<0.01) in hepatic malondialdehyde (MDA) level and the liver function enzymes alkaline phosphatase (ALP), alanine amino transferase (ALT) and aspartate amino transferase (AST) level in the serum. It also caused a marked reduction (p<0.01) in glutathione level, significant decrease (p<0.01) in the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT) and significant damage to the hepatocytes. Recovery diets of protein alone and protein supplemented with T. occidentalis had significant effects on all the parameters. The MDA level and the serum liver function enzymes were significantly reduced (p<0.01), glutathione and antioxidant enzymes levels were markedly increased (p<0.01) and a highly significant hepatocyte healing observed in the histology images. The highest recovery was however observed in group C. Results indicate the restorative ability of T. occidentalis in treatment of oxidative stress induced liver damage in PEM rats.
 
 
 
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