Information disclosure can reduce information asymmetry between health care providers and patients, thus improving both patient safety and medical quality. The National Bureau of Health Insurance (NBHI) inTaiwancurren...Information disclosure can reduce information asymmetry between health care providers and patients, thus improving both patient safety and medical quality. The National Bureau of Health Insurance (NBHI) inTaiwancurrently publishes health-related information online in order to enhance service efficiency and enable the public to monitor the country’s medical system. A data mining technique, classification and regression tree (CART), is used in this work to investigate online public quality information to compare the characteristics of hospital. The hospital quality indicators and characteristics data are available on the websites of the NBHI (http://www.nhi.gov.tw/AmountInfoWeb/Index.aspx) and the Department of Health (http://www.doh.gov.tw/). The full classification and regression tree presented in this work, grown using the hospitals’ quality medical indicators and characteristic values, classifies all hospitals into seven groups. The rate of stays longer than 30 days, which is the dependent variable in this study, is most influenced by the number of medical staff. This reflects the fact that the fewer medical staffs that are employed, the smaller the hospital is, and patients who are likely to have longer stays tend to go to the medium or large hospitals. Policy makers should work to decrease or eliminate persistent healthcare disparities among different socioeconomic groups and offer more online healthrelated services to reduce information asymmetry between health care providers and patients.展开更多
One of the leading cancers for both genders worldwide is lung cancer.The occurrence of lung cancer has fully augmented since the early 19th century.In this manuscript,we have discussed various data mining techniques t...One of the leading cancers for both genders worldwide is lung cancer.The occurrence of lung cancer has fully augmented since the early 19th century.In this manuscript,we have discussed various data mining techniques that have been employed for cancer diagnosis.Exposure to air pollution has been related to various adverse health effects.This work is subject to analysis of various air pollutants and associated health hazards and intends to evaluate the impact of air pollution caused by lung cancer.We have introduced data mining in lung cancer to air pollution,and our approach includes preprocessing,data mining,testing and evaluation,and knowledge discovery.Initially,we will eradicate the noise and irrelevant data,and following that,we will join the multiple informed sources into a common source.From that source,we will designate the information relevant to our investigation to be regained from that assortment.Following that,we will convert the designated data into a suitable mining process.The patterns are abstracted by utilizing a relational suggestion rule mining process.These patterns have revealed information,and this information is categorized with the help of an Auto Associative Neural Network classification method(AANN).The proposed method is compared with the existing method in various factors.In conclusion,the projected Auto associative neural network and relational suggestion rule mining methods accomplish a high accuracy status.展开更多
It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting ...It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting and amending anomalous samples was proposed. Taking full advantage of wavelet analysis’ properties of multi-resolution and local analysis, this approach is able to detect and amend anomalous samples effectively. To realize the rapid numeric computation of wavelet translation for a discrete sequence, a modified algorithm based on Newton-Cores formula was also proposed. The experimental result shows that the approach is feasible with good result and good practicality.展开更多
文摘Information disclosure can reduce information asymmetry between health care providers and patients, thus improving both patient safety and medical quality. The National Bureau of Health Insurance (NBHI) inTaiwancurrently publishes health-related information online in order to enhance service efficiency and enable the public to monitor the country’s medical system. A data mining technique, classification and regression tree (CART), is used in this work to investigate online public quality information to compare the characteristics of hospital. The hospital quality indicators and characteristics data are available on the websites of the NBHI (http://www.nhi.gov.tw/AmountInfoWeb/Index.aspx) and the Department of Health (http://www.doh.gov.tw/). The full classification and regression tree presented in this work, grown using the hospitals’ quality medical indicators and characteristic values, classifies all hospitals into seven groups. The rate of stays longer than 30 days, which is the dependent variable in this study, is most influenced by the number of medical staff. This reflects the fact that the fewer medical staffs that are employed, the smaller the hospital is, and patients who are likely to have longer stays tend to go to the medium or large hospitals. Policy makers should work to decrease or eliminate persistent healthcare disparities among different socioeconomic groups and offer more online healthrelated services to reduce information asymmetry between health care providers and patients.
基金support from Taif University Researchers supporting Project Number(TURSP-2020/215),Taif University,Taif,Saudi Arabia.
文摘One of the leading cancers for both genders worldwide is lung cancer.The occurrence of lung cancer has fully augmented since the early 19th century.In this manuscript,we have discussed various data mining techniques that have been employed for cancer diagnosis.Exposure to air pollution has been related to various adverse health effects.This work is subject to analysis of various air pollutants and associated health hazards and intends to evaluate the impact of air pollution caused by lung cancer.We have introduced data mining in lung cancer to air pollution,and our approach includes preprocessing,data mining,testing and evaluation,and knowledge discovery.Initially,we will eradicate the noise and irrelevant data,and following that,we will join the multiple informed sources into a common source.From that source,we will designate the information relevant to our investigation to be regained from that assortment.Following that,we will convert the designated data into a suitable mining process.The patterns are abstracted by utilizing a relational suggestion rule mining process.These patterns have revealed information,and this information is categorized with the help of an Auto Associative Neural Network classification method(AANN).The proposed method is compared with the existing method in various factors.In conclusion,the projected Auto associative neural network and relational suggestion rule mining methods accomplish a high accuracy status.
基金Project(50374079) supported by the National Natural Science Foundation of China
文摘It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting and amending anomalous samples was proposed. Taking full advantage of wavelet analysis’ properties of multi-resolution and local analysis, this approach is able to detect and amend anomalous samples effectively. To realize the rapid numeric computation of wavelet translation for a discrete sequence, a modified algorithm based on Newton-Cores formula was also proposed. The experimental result shows that the approach is feasible with good result and good practicality.
