Background: In this paper, a four layer model of the simultaneous and coaxial flow of moist air, mucus, mixture of mucin and periciliary liquid and serous fluid (assumed to be incompressible and Newtonian fluids) in a circular tube under time dependent pressure gradient representing prolonged cough is analyzed to study the mucus transport in an airway in the presence of prolonged cough. It is assumed that air and mucus flow under quasi steady state turbulent conditions while the mixture of mucin and periciliary liquid and serous layer surrounding mixture layer flows under unsteady laminar condition in presence of immotile cilia carpet. Result: It is shown that the mucus transport increases as the viscosity of serous fluid decreases. Also the mixture and serous fluid flow rates increase as the viscosity of serous fluid decreases. It is also observed that the effect of resistance to flow by serous fluid in the cilia bed is to decrease flow rates. The flow rates of mucus and mixture of mucin and periciliary fluid increase as the viscosity of mixture decreases also air and mixture of mucus and periciliary fluid flow rates increase as the thickness of mixture increases. Conclusion: As the thickness of mucus increases its flow rate increases on the other hand the mixture flow rate, mucus and serous fluid flow rate decreases with the increase of the mixture thickness. Bangladesh Journal of Medical Science Vol.19(1) 2020 p.53-63

Background: SARS-coronavirus-2 is a new virus infecting people and causing COVID-19 disease. The disease is causing a worldwide pandemic. Although some people never develop any signs or symptoms of disease when they are infected, other people are at very high risk for severe disease and death. Objective: If we’re able to intervene to prevent even some transmission, we can dramatically reduce the number of cases. And this is the public health goal for controlling COVID-19. Methods: This article initializes an approach for comparatively accurate values prediction of new cases and deaths for a particular day in order to be considered for preventive measures. The three statistical analysis methods considered for forecasting are Fbprophet, Moving average and the Autoregressive Integrated Moving Average algorithm. Results: The results obtained are in-line with the past and present trend of COVID-19 data collected from WHO website. Conclusion: The output is satisfactory for further consideration. Bangladesh Journal of Medical Science Vol.20(5) 2021 p.85-96

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Health care is considered as the fundamental right of every citizen and it is principle duty of every country to provide good health care facilities. Many developed countries spend substantial amount of gross domestic product (GDP) on healthcare. In this chapter, we discuss kernel based machine learning techniques, i.e., k-PCA (Kernel principal component analysis) and its related properties with a aim to prescribe cost effective treatments and easy diagnosis of diseases. This objective could be met only by the serious collaboration between physician and data scientist. We discussed that how we could construct a kernel and exact features based on the given dataset. Also, we compared the proposed method with the other methods. For the sake of easy understanding, applications of the proposed method are included in the text.

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