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مقالات فارسیISIکنفرانسهاژورنالها

Predicting Mortality of COVID-۱۹ Patients based on Data Mining Techniques

محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 11، شماره: 5
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 54

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استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:
https://civilica.com/doc/1892566

شناسه ملی سند علمی:

JR_JBPE-11-5_011

تاریخ نمایه سازی: 30 دی 1402

چکیده مقاله:

If Coronavirus (COVID-۱۹) is not predicted, managed, and controlled timely, the health systems of any country and their people will face serious problems. Predictive models can be helpful in health resource management and prevent outbreak and death caused by COVID-۱۹. The present study aimed at predicting mortality in patients with COVID-۱۹ based on data mining techniques. To do this study, the mortality factors of COVID-۱۹ patients were first identified based on different studies. These factors were confirmed by specialist physicians. Based on the confirmed factors, the data of COVID-۱۹ patients were extracted from ۸۵۰ medical records. Decision tree (J۴۸), MLP, KNN, random forest, and SVM data mining models were used for prediction. The models were evaluated based on accuracy, precision, specificity, sensitivity, and the ROC curve. According to the results, the most effective factor used to predict the death of COVID-۱۹ patients was dyspnea. Based on ROC (۱.۰۰۰), accuracy (۹۹.۲۳%), precision (۹۹.۷۴%), sensitivity (۹۸.۲۵%) and specificity (۹۹.۸۴%), the random forest was the best model in predicting of mortality than other models. After the random forest, KNN۵, MLP, and J۴۸ models were ranked next, respectively. Data analysis of COVID-۱۹ patients can be a suitable and practical tool for predicting the mortality of these patients. Given the sensitivity of medical science concerning maintaining human life and lack of specialized human resources in the health system, using the proposed models can increase the chances of successful treatment, prevent early death and reduce the costs associated with long treatments for patients, hospitals and the insurance industry.

کلیدواژه ها:

Mortality ، COVID-۱۹ ، Data mining ، Prediction

نویسندگان

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PhD Candidate, Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

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PhD, Department of Computer Engineering, Faculty of Engineering, Shahid Bahonar University Kerman, Kerman, Iran

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MD, PhD, Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

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PhD, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran

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MSc, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

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