SARS-CoV-2 infections continue to cause severe disease, particularly in older people and individuals with comorbidities. Understanding risk factors that make individuals vulnerable for severe disease is key for the management of disease and resources. Machine Learning-based approach was employed to predict disease outcomes in a cohort on 437 COVID-19 patients in Oman. Patient data including various blood parameters were obtained from the main government hospital in Oman. Various machine learning algorithms were used to extract the hidden patterns from the obtained datasets. The experimental results showed that age, gender, chronic kidney disease and multiple blood parameters are risk factors for poor prognosis in older patients. Moreover, male patients with blood type O-positive and A-positive are more vulnerable for severe disease as compared to female counterparts. The study revealed the important risk factors that can be used to improve management of COVID-19 cases.
|حالة النشر||In preparation - 2022|