This article explores the use of fuzzy logic in the medical field. While giving a comparison of classic and fuzzy logic we present the various uses of the applications made possible by fuzzy logic, focusing on diagnosis and treatment. The ever evolving technology making the line between medicine and technology thinner every year, is helping to make the treatment of disease and the mending of injury easier for medical professionals. We also propose several questions that arise from, and may by answered by, fuzzy logic and its applications.
This article explores the use of fuzzy logic in the medical field. While giving a comparison of classic and fuzzy logic we present the various uses of the applications made possible by fuzzy logic, focusing on diagnosis and treatment. The ever evolving technology making the line between medicine and technology thinner every year, is helping to make the treatment of disease and the mending of injury easier for medical professionals. We also propose several questions that arise from, and may by answered by, fuzzy logic and its applications.
It is impossible to pinpoint the exact moment at which computational biology became a discipline of its own, but one could say that it was in 1997 when the society of computational biology was formed. Regardless of its exact birthday, the research community has rapidly adopted computational biology and its applications are being vigorously explored. The study and application of medicine is a dynamic challenge. Changes in medicine usually take place as a result of new knowledge acquired through observation and experimentation. When a tamping rod 1-inch thick went through Phineas Gage’s head in 1848, his survival gave the medical field an unusual opportunity to observe behavior of a person missing their prefrontal cortex. This observation lead to the short-lived psychosurgical procedure known as a lobotomy, which attempted to change a person’s behavior by separating two portions of a person’s brain (Pols, 2001). Countless observations, experiments and mistakes represent how almost all medical knowledge has been acquired. The relatively new field of computational biology offers a nontraditional approach to contribute to the medical body of knowledge. Computational biology is a new field combining biology, computer science, and mathematics to solve problems that are unworkable with traditional biological techniques. It includes traditional areas such as systems biology, molecular biology, biochemistry, biophysics, statistics, and computer science, as well as recently developed disciplines including bioinformatics and computational genomics. Algorithms, which are able to closely model biological behavior, validate the medical understanding of the observed processes and can be used to model scenarios that might not be able to be physically reproduced. The goal of computational biology is to use mathematics and computer science to model biological systems on the molecular level. Instead of taking on large complex systems, computational biology is starting small, literally. Modeling problems in molecular biology and biochemistry is a far less daunting task. At a microscopic level, patient’s characteristics drop out of the equation and all information behavior affecting is known. This creates a deterministic model which, given the same input, will always produce the same output. Some of the major subdisciplines of computational biology are computational genomics, systems biology, protein structure prediction, and evolutionary biology, all of which model microscopic structures.
This study looks at the contribution that consuming fast food may make to the rise in
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