Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Medicine and Health Sciences
Covid-19 Peak Immunity Values Seem To Follow Lognormal Distribution, Julio Urenda, Olga Kosheleva, Vladik Kreinovich, Tonghui Wang
Covid-19 Peak Immunity Values Seem To Follow Lognormal Distribution, Julio Urenda, Olga Kosheleva, Vladik Kreinovich, Tonghui Wang
Departmental Technical Reports (CS)
For the current pandemic, an important open problem is immunity: do people who had this disease become immune against further infections? In the immunity study, it is important to know how frequent are different levels of immunity, i.e., what is the probability distribution of the immunity levels. Different people have different rates of immunity dynamics: for some, immunity gets to the level faster, for others the immunity effect is slower. Similarly, in some patients, immunity stays longer, it others, it decreases faster. In view of this, an important characteristic is peak immunity. A recent study provides some statistics on the …
Scale-Invariance-Based Pre-Processing Drastically Improves Neural Network Learning: Case Study Of Diagnosing Lung Dysfunction In Children, Nancy Avila, Julio Urenda, Nelly Gordillo, Vladik Kreinovich
Scale-Invariance-Based Pre-Processing Drastically Improves Neural Network Learning: Case Study Of Diagnosing Lung Dysfunction In Children, Nancy Avila, Julio Urenda, Nelly Gordillo, Vladik Kreinovich
Departmental Technical Reports (CS)
To adequately treat different types of lung dysfunctions in children, it is important to properly diagnose the corresponding dysfunction, and this is not an easy task. Neural networks have been trained to perform this diagnosis, but they are not perfect in diagnostics: their success rate is 60%. In this paper, we show that by selecting an appropriate invariance-based pre-processing, we can drastically improve the diagnostic success, to 100% for diagnosing the presence of a lung dysfunction.