Browsing by Author "Kabir Opeyemi Olorede"

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    A novel hybrid dimension reduction technique for efficient selection of bio-marker genes and prediction of heart failure status of patients
    (Scientific African, 2021-05-02) Kazeem Adesina Dauda; Kabir Opeyemi Olorede; Samuel Adewale Aderoju
    This study highlighted and provided a conceptual framework of a hybridized dimension reduction by combining Genetic Algorithms (GA) and Boruta Algorithm (BA) with Deep Neural Network (DNN). Among questions left unanswered sufficiently by both computational and biological scientists are: which genes among thousand of genes are statistically relevant to the prediction of patients’ heart rhythm? and how they are associated with heart rhythm? A plethora of models has been proposed to reliably identify core informative genes. The premise of this present work is to address these limitations. Five distinct micro-array data on heart diseases have been taken into consideration to observe the prominent genes. We form three distinct set two-way hybrids between Boruta Algorithm and Neural Network (BANN); Genetic Algorithm and Deep Neural Network (GADNN) and Boruta Algorithm and Deep Neural Network (BADNN), respectively, to extract highly differentially expressed genes to achieve both better estimation and clearer interpretation of the parameters included in these models. The results of the filtering process were observed to be impressive since the technique removed noisy genes. The proposed BA algorithm was observed to select minimum genes in the wrapper process with about 80% of the five datasets than the proposed GA algorithm with 20%. Moreover, the empirical comparative results revealed that BADNN outperformed other proposed algorithms with prediction ac curacy of 97%, 87%, and 100% respectively. Finally, this study has successfully demonstrated the utility, versatility, and applicability of hybrid dimension reduction algorithms (HDRA) in the realm of deep neural networks.
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    Competing Risk Modeling Using Cumulative Incidence Function: Application to Recurrent Bladder Cancer data
    (FUOYE Journal of Engineering and Technology, 2018) Kabir Opeyemi Olorede
    In this study, the effects of some clinical variables on the survival times of patients with bladder cancer were examined. The effects of these variables on sub-distribution of the failure types were determined using the proportional sub-distribution hazards regression model described in Fine and Gray (1999). Published dataset on 294 bladder cancer patients with four clinical outcomes were analyzed using Cumulative Incidence Function approach. The four outcomes included 184 (64%) patients that experienced recurrence of bladder cancer after receiving chemotherapy treatments. Two patients died of bladder cancer while 27 patients died of other causes and the remaining 76 patients did not experienced any of these three outcomes, and as a result, were considered censored. Among the covariates considered, only the patients’ initial number of tumors and initial size of tumor were incorporated into our analysis due to high proportion of missing observations in others. Results from this work showed that, patients with tumour recurrence have highest risk of dying than those from other causes. Further results showed that, the number of tumor was positively associated with the recurrence of cancer of the bladder. However, the size of the tumor did not demonstrate a significant effect on the patients’ survival time. It can therefore, be concluded that patients with tumor recurrence have low probability of survival from bladder cancer than patients that experienced other events. Above all, number, but not size of tumor could adversely affect the survival time of bladder cancer patients, especially those with tumor recurrence after bladder cancer treatment.
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    Hydration Status in Nigeria: A Cross-Sectional Study
    (Pakistan Journal of Nutrition, 2014) Yunusa Olufadi; Alfred B. O. Soboyejo; Kabir Opeyemi Olorede; Kazeem Adesina Dauda
    Most literatures on daily water intake are focused on developed countries and to our knowledge; there is limited information on the hydration status of Nigerians. Our objective was to describe daily water intake (DWI) among Nigerian students, develop a model for the prediction of students’ DWI and examine the association between DWI and four predictor variables. Data on DWI for 150 students aged 18-26 years were collected through a survey conducted at Kwara State University in February, 2013 together with information on their age, weight, gender and awareness of dieticians’ recommendation. Our results indicates that students’ DWI varies by gender with male students drinking more than their female counterparts; although, the awareness rate is higher in females than males. We found that nearly half of participants (44%) drank less than 2.7 L of water/day, 25% between 2.7 and 3.7 L/day and 31% reported drinking more than 3.7 L of water/day. Results also revealed that students’ DWI decline with age but increases with weight and one-in-two of the students are unaware of the dangers of poor hydration. Arguably, this study is the first description of DWI among Nigerian students and fills the gap in the literature by developing two models for the prediction of students’ DWI. In light of the significance of the knowledge and awareness of Dieticians’ recommendation on DWI (as evidence in this study) and the low awareness rate existing among the students; nutrition and health promotion program on the benefits of adequate DWI by schools and health organizations is extremely important. This has the potential of improving the health of students.