Big Data and Machine Learning Based Early Chronic Kidney Disease Prediction

Asra Fatima, Shireen Fatima, Ayesha Kiran
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Abstract

A chronic kidney disease, sometimes called a chronic renal disease, is characterized by a gradual decline in kidney purpose or abnormal kidney purpose which continues for months or even years. Patients with a domestic past of chronic kidney disease (CKD), high BP, or other kidney-related conditions are often the first to have chronic kidney disease (CKD) identified during screenings. Consequently, effective illness prevention and therapy rely on early prediction. Methods from the field of machine learning, including XGBoost, KNN, Decision Tree, and Random Forest, are being considered for use in this CKD project. The final product uses the fewest characteristics possible to determine whether the patient has chronic kidney disease (CKD).
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基于大数据和机器学习的早期慢性肾病预测
慢性肾脏病,有时也称为慢性肾脏病,其特点是肾功能逐渐减退或肾功能异常,持续数月甚至数年。国内既往患有慢性肾脏病(CKD)、高血压或其他肾脏相关疾病的患者,往往在筛查中最先发现慢性肾脏病(CKD)。因此,有效的疾病预防和治疗有赖于早期预测。目前正在考虑将 XGBoost、KNN、决策树和随机森林等机器学习领域的方法用于该 CKD 项目。最终产品将使用尽可能少的特征来确定患者是否患有慢性肾病(CKD)。
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