Optimization the Mathematical and Computational Approaches to Understanding the Medical Science Applications

Abstract

Computing is the backbone of modern healthcare systems, it not only cut-downs the associated treatment and medicine costs but also decreases the logistics requirements simple mathematics is used effectively by people in all walks of life to assist decision making. However, in this paper it is argued that many, so called, applied mathematicians affiliated with university mathematics departments all too often do not apply mathematics to anything in particular. Although there is the national appeal of relevance to an application for the equations under study, applied mathematics has come to mean something completely different than really applying mathematics to solve an important the problem in another discipline. Even ‘mathematical modeling’ is often observed to involve the development of ‘neat’ equations which are stated to be loosely linked to something people will care about but is presented with esoteric and obscure mathematics which is not accessible to stakeholders in the application of the problem. It is suggested that simple models that directly answer questions of relevance are always better than complex models that are not influential, unrealistic, or irrelevant and that experts in the area of application must have integral roles in the entire modeling process, including the design of research questions, ensuring realism of model structures, informing parameter estimates, and the presentation and communication of results.

Keywords: Computing, Medical Applications, Medical Image, Polynomials.