SMOTE-NC and gradient boosting imputation based random forest classifier for predicting severity level of covid-19 patients with blood samples

Abstract

An increase in the number of patients and death rates make Covid-19 a serious pandemic situation. This problem has effects on health security, economical security, social life, and many others. The long and unreliable diagnosis process of the Covid-19 makes the disease spread even faster. Therefore, fast and efficient diagnosis is significant for dealing with this pandemic. Computer-aided medical diagnosis systems are very common applications and due to the importance of the problem, providing accurate predictions is required. In this study, blood samples of patients from Einstein Hospital in Brazil has collected and used for prediction on the severity level of Covid-19 with machine learning algorithms. The study was constructed in two stages; in stage-one, no preprocessing method has applied while in stage-two preprocessing has emphasized for achieving better prediction results. At the end of the study, 0.98 accuracy was obtained with the tuned Random Forest algorithm and several preprocessing methods.

Predictive models for COVID-19 detection using routine blood tests and machine learning

“… Both low/high hemoglobin levels can indicate certain diseases. [][ []19, 26, 28 []] [] [] [] [][ []29, 30, 31 []] [] [] [] [][ []33, 34, 35 []] [] [] [] [][ []36, 37, 38 []] [] [] [] [][ []39, 40, 41 []] [] [] [] [][ []42, 44, 45 []] [] [] [] [][ []46, 47, 48 []] [] [] [] [][ []49, 50, 51 []] [] [] [] [][ []35, 51 []] [] [] [] PLT Platelets Platelets are a component of blood whose function is to react to bleeding from blood vessel injury by clumping, that plays a major role in blood clotting. PLT reflects a pathology risk/severity, for example, cancer [ 87 ].…”

“…PLT reflects a pathology risk/severity, for example, cancer [ 87 ]. [][ []4, 23, 26 []] [] [] [] [][ []28, 29, 30 []] [] [] [] [][ []31, 32, 33 []] [] [] [] [][ []35, 36, 37 []] [] [] [] [][ []38, 39, 40 []] [] [] [] [][ []42, 43, 44 []] [] [] [] [][ []45, 46, 47 []] [] [] [] [][ []50, 51, 52 []] [] [] [] [][ []23, 28 []] [] [] [] [][ []30, 38 []] [] [] [] [][ []39, 51 []] [] [] [] RBC Red blood cells Red blood cells are the most common type of blood cells that carry oxygen to the body tissues via blood flow through the circulatory system. Low/high RBC levels indicate health problems, for example liver disease.…”

“… [][ []4, 19, 26 []] [] [] [] [][ []28, 29, 30 []] [] [] [] [][ []31, 33, 34 []] [] [] [] [][ []35, 36, 38 []] [] [] [] [][ []39, 40, 41 []] [] [] [] [][ []42, 44, 45 []] [] [] [] 46 , 47 , 49 50 , 51 , 52 54 , 55 , 56 [ 57 ] [][ []34, 39 []] [] [] [] [][ []41, 44 []] [] [] [] [][ []50, 51 []] [] [] [] [][ []52, 55 []] [] [] [] [][ []56, 57 []] [] [] [] MCH Mean Corpuscular Hemoglobin The mean corpuscular hemoglobin is the average mass of HGB per a RBC in a blood sample. [][ []19, 26, 27 []] [] [] [] [][ []28, 29, 30 []] [] [] [] [][ []31, 32, 33 []] [] [] [] [][ []34, 35, 36 []] [] [] [] [][ []37, 46, 52 []] [] [] [], [ 53 ] MCHC Mean Corpuscular Hemoglobin Concentration The mean corpuscular hemoglobin concentration characterizes an average concentration of HGB in a RBC. MCHC also reflects the amount of hemoglobin per unit volume in a single red blood cell ...…”

“…WBC are the cells of the immune system involved in protecting the body against infectious disease. [][ []4, 19, 26 []] [] [] [] [][ []27, 28, 29 []] [] [] [] [][ []30, 31, 32 []] [] [] [] [][ []33, 34, 35 []] [] [] [] [][ []36, 37, 38 []] [] [] [] [][ []39, 40, 41 []] [] [] [] [][ []42, 43, 44 []] [] [] [] [][ []45, 46, 47 []] [] [] [] [][ []50, 51, 52 []] [] [] [] [][ []53, 54, 55 []] [] [] [] [][ []56, 57 []] [] [] [] [4,26]] [28,30]] [38,39]] [51,52]] 53 ,56] [ 57 ] BAY Basophils Basophils are a type of white blood cells. Basophils have granules containing biologically active substances, with the help of which they regulate immune responses.…”

Light Gradient Boosting with Hyper Parameter Tuning Optimization for COVID-19 Prediction

“…Blood samples from sufferers from Einstein Hospital in Brazil were amassed and used for prediction of the severity of COVID-19 with studying algorithms. The Tuned Random Forest algorithm [15] produced an accuracy of 0,98 with numerous preprocessing methods.…”