Proposed Method for Predicting COVID-۱۹ Severity in Chronic Kidney Disease Patients Based on Ant Colony Algorithm and CHAID
- سال انتشار: 1401
- محل انتشار: مجله علمی پژوهشی دانشگاه علوم پزشکی زنجان، دوره: 30، شماره: 143
- کد COI اختصاصی: JR_ZUMS-30-143_006
- زبان مقاله: انگلیسی
- تعداد مشاهده: 135
نویسندگان
Isfahan Kidney Diseases Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
چکیده
Background and Objective: The COVID-۱۹ pandemic is a phenomenon that has infected and killed many people worldwide. Underlying diseases such as diabetes mellitus, heart failure, and chronic kidney disease (CKD) can affect the severity of COVID-۱۹ and aggravate patients' condition. This study aimed to predict the severity of the COVID-۱۹ disease in CKD patients by combining feature selection and classification methods. Materials and Methods: This study was conducted between March ۲۰۲۱ and September ۲۰۲۱ in Isfahan University of Medical Sciences. The data set includes ۸۳ traits of ۷۲ kidney transplant patients, ۲۳۱ kidney failure patients, and ۱۰۵ dialysis patients. The data set has ۷۷ input attributes, including age, sex, diabetes mellitus, hypertension, ischemic heart disease, chronic lung disease, and kidney transplant. In the proposed method, the combination of ant colony algorithm and the CHAID method has been used. Results: The combination of the ant colony algorithm and CHAID method leads to better performance than CHAID alone. A total of ۲۲ rules were extracted, of which ۶ rules with a confidence of more than ۶۰% were introduced as selected rules. The most reliable rule states that if a person has CKD stage ۵, is not undergoing dialysis (۵ND), and is short of breath, in ۸۱% of cases the type of COVID-۱۹ disease will be severe. Conclusion: In this study the severity of COVID-۱۹ disease in kidney patients was measured using variables including age, diabetes mellitus, blood pressure, CKD stage, etc. The results showed that high levels of kidney disease can lead to severe COVID-۱۹.کلیدواژه ها
Data mining, Prediction, Kidney disease, COVID-۱۹اطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.