Machine Learning for IgG Identification in the Absence of Infection to Isolate Autoimmune Activity
$ 42.5
Description
As autoimmune diseases present both a physiological and psychiatric challenge due to symptom belittlement for roughly 10% of the world's population, machine learning can be used to help distinguish between autoimmune illness and acute infection via immunoglobulin G (IgG) detection. This solution could help isolate conditions that are often misdiagnosed as psychosomatic, thus reducing stigma against what is often described as "invisible illness". This book provides a foundational Python code for an algorithm that would analyze the blood serum for abnormal IgG levels in the presence of normal or low procalcitonin (PCT) to isolate autoimmunity from bacterial infection and in the absence of a high lymphocyte count and a low neutrophil count to isolate from viral infection.