Vinothini Arumugam^*, S. Baghavathi Priya

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 947-959, 2022, DOI:10.32604/iasc.2022.018654

Abstract Nowadays, Chronic Kidney Disease (CKD) is one of the vigorous public health diseases. Hence, early detection of the disease may reduce the severity of its consequences. Besides, medical databases of any disease diagnosis may be collected from the blood test, urine test, and patient history. Nevertheless, medical information retrieved from various sources is diverse. Therefore, it is unadaptable to evaluate numerical and nominal features using the same feature selection algorithm, which may lead to fallacious analysis. Applying machine learning techniques over the medical database is a common way to help feature identification for CKD prediction. In this paper, a novel… More >

Hemant Petwal^*, Rinkle Rani

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2563-2582, 2021, DOI:10.32604/cmc.2021.017548

Abstract In the healthcare system, a surgical team is a unit of experienced personnel who provide medical care to surgical patients during surgery. Selecting a surgical team is challenging for a multispecialty hospital as the performance of its members affects the efficiency and reliability of the hospital’s patient care. The effectiveness of a surgical team depends not only on its individual members but also on the coordination among them. In this paper, we addressed the challenges of surgical team selection faced by a multispecialty hospital and proposed a decision-making framework for selecting the optimal list of surgical teams for a given… More >

Lina Wang^1,2,*, Qixiang Zhang¹, Xiling Niu¹, Yongjun Ren³, Jinyue Xia⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1765-1781, 2021, DOI:10.32604/cmc.2021.017516

Abstract Outlier detection is a key research area in data mining technologies, as outlier detection can identify data inconsistent within a data set. Outlier detection aims to find an abnormal data size from a large data size and has been applied in many fields including fraud detection, network intrusion detection, disaster prediction, medical diagnosis, public security, and image processing. While outlier detection has been widely applied in real systems, its effectiveness is challenged by higher dimensions and redundant data attributes, leading to detection errors and complicated calculations. The prevalence of mixed data is a current issue for outlier detection algorithms. An… More >

Maojun Zhang^1,2, Jiajin Yao¹, Zhonghang Xia³, Jiangxia Nan^1,*, Cuiqing Zhang¹

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1233-1244, 2019, DOI:10.32604/cmc.2019.06118

Abstract It is well known that economic policy uncertainty prompts the volatility of the high-yield bond market. However, the correlation between economic policy uncertainty and volatility of high-yield bonds is still not clear. In this paper, we employ GARCH-MIDAS models to investigate their correlation with US economic policy uncertainty index and S&P high-yield bond index. The empirical studies show that mixed volatility models can effectively capture the realized volatility of high-yield bonds, and economic policy uncertainty and macroeconomic factors have significant effects on the long-term component of high-yield bonds volatility. More >