PREDICTING COVID-19 INFECTED PATIENTS BASED ON MACHINE LEARNING IN HEALTHCARE MODEL

PREDICTING COVID-19 INFECTED PATIENTS BASED ON MACHINE LEARNING IN HEALTHCARE MODEL 5 Aspects of the present disclosure relate to a method (100) for prediction of COVID-19 based on machine learning. The invention provides a CT image-based quantitative analysis method (100) for COVID-19. The method (100) comprises the step of initially creating (102) a machine learning model. After the creating (102) the machine learning model, plurality of CT images are inputted into the machine learning model. After the images are inputted (104), 10 generating (106) 3D focus data for each of the CT images. Based on the 3D focus data, a quantification factor is calculated (108) for each of the CT image. Based on this quantification it is analyzed (110) whether the patient is suffering from COVID-19 or not. The doctor can also visually observe the information such as the size, position of the lesion region. (FIG. 1 will be the reference figure) - 13 - rage 1 01 1 Creating machine learning model Inputting images into the machine learning model 1 104 Generating 3D focus data106 Calculating quantification factor for CT images Analyzing by comparing the quantification factor with the critical threshold value 110 FIG. 1. Flowchart of method based on machine learning for the detection of COVID-19 patients using CT imaging