ABSTRACT
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is gradually valued due to its high prevalence, high risk, and high mortality. Alternative to the polysomnography (PSG) diagnosis, the proposed method assesses the subject's degree of illness considering the supply chain and Industry 5.0 requirement efficiently and accurately. This article uses the blood oxygen saturation (SpO(2)) signal count of the number of apnea or hypoventilation events during the sleep of the subject, calculating the apnea-hypopnea index (AHI) and the subject's disease level. SpO(2) signals are used to extract 35-D features based on the time domain, including approximate entropy, central tendency measure, and Lempel-Ziv complexity to accelerate the diagnosis process in supply chains. The feature selection process is reduced from 35 to 7 dimensions that benefits to the implementation in the practical supply chains in Industry 5.0 by extracting the extracted features. This article applies Pearson correlation coefficient selection, based on minimum redundancy-maximum correlation algorithm selection, and a wrapper based on the backward search algorithm. The accuracy rate is 86.92%, and the specificity is 90.7% under the selected random forest classifier. A random forest classifier was used to calculate the AHI index, and a linear regression analysis was performed with the AHI index obtained from the PSG. The result reaches a 92% accuracy rate in assessing the prevalence of OSAHS, satisfying the industrial deployment.
ABSTRACT
The original version of this article contained errors in author affiliations and Figures. The correct information author affiliations and Figures should be as follows. The authors would like to apologize for any inconvenience caused.
ABSTRACT
The original version of this article contained errors in author affiliations and Figures. The correct information author affiliations and Figures should be as follows. The authors would like to apologize for any inconvenience caused.
ABSTRACT
Since December 2019, an outbreak of a new coronavirus, COVID-19, infection has been taking place. At present, COVID-19 has spread to most countries worldwide. The latest evidence suggests that cytokine storm syndrome (CSS) is an important cause of the transition from mild to critical pneumonia and critically ill patients' death. The sudden exacerbation of COVID-19 may be related to a cytokine storm. Therefore, early identification and active treatment of CSS may play very important roles in improving the patients' prognosis, and these tasks are given attention in the current treatment of new Coronavirus pneumonia. However, there is still no specific medicine for this purpose. This article reviews cytokine storms and conducts an exploratory review of pharmacotherapy for cytokine storms to provide a reference for clinical treatment.