Preventing Pathology through a Mathematical Analysis

Abstract

Research Description and Goals Psychiatry seems to be one of the few areas of medicine, perhaps the only one, in which treatments such as talk therapies, medication, and peer support are not well supported by more efective technological alternatives, such as ECT (electroconvulsive therapy), which alters brain functions with small, external electrical stimulations, or TMS (transcranial magnetic stimulation), which involves the use of a special electromagnetic device that sends short impulses to the brain. Often, diagnoses and therapies are left to the experience and subjective evaluation of the psychiatrist, whose accuracy is subject to constant criticism of other, skeptic psychiatrists with a diferent point of view. Conversely, technology nowadays is becoming more and more involved in the scientifc community, leading research to solve modern and controversial topics. In the section Platelet's Fatty Acids and Diferential Diagnosis of Major Depression and Bipolar Disorder through the Use of an Unsupervised Competitive-Learning Network Algorithm (SOM) of the article Open Journal of Depression, Serena Benedetti (et al.) discusses how, from a simple blood sample, it is possible to calculate the quantity of polyunsaturated fatty acids (lipids mostly found in seeds, nuts, or fsh) that are present in the human body's platelet membranes, which are small red blood cells that prevent bleeding. The research proposal is well-founded with the help of a mathematical analysis through a nonlinear self-organizing map (SOM) that allows a better and more concise use of the information contained in the platelet. The combined application that the project proposes, therefore, could lead to an almost perfect diagnosis of the pathology aficting the patient.