CUKUROVA 8th INTERNATIONAL SCIENTIFIC RESEARCHES CONFERENCE 15 - 17 April 2022 / Adana, TURKEY, Adana, Türkiye, 15 - 17 Nisan 2022, ss.1-10
ABSTRACT
In recent years, classification methods, one of the main applications of machine learning, are
widely used in many fields. Among these areas, health is an important area where machine
learning studies are applied successfully. In this study, it is aimed to develop models that
predict disease stage in people with Covid-19 diagnosis using machine learning (ML)
classification methods. Covid-19 is an epidemic disease that was declared a pandemic by the
World Health Organization in March 2020 and caused the death of millions of people around
the world. Today, millions of people still suffer from this disease and face death. In addition
to the problems of medical system inadequacies such as lack of beds, intensive care
occupancy, and respiratory (ventilator) device shortages, the pandemic has also left healthcare
workers faced with the overwhelming burden of patients. For this reason, the ability to detect
the deterioration of the patient by early determination of the disease stage during their stay in
the hospital for Covid-19 patients is very important for hospital management. Within the
scope of the study, clinical and laboratory data of Covid-19 patients at hospital admission
were used. For the data set, models that provide prediction of disease stage were obtained by
using the classification-based machine learning algorithms Logistic Regression, Random
Forest and Support Vector Machines. With the models obtained, the hospital management
will be informed about the number of beds that will be required for moderate, severe and
critical Covid-19 patients and the need for detailed human resource power to take various
precautions in advance.
Keywords: Covid-19, Supervised Learning, Logistic Regression, Random Forests, Support
Vector Machines