The accumulating amounts of data are making traditional analysis methods impractical. Novel tools employed in Data Mining (DM) provide a useful alternative framework that addresses this problem. This research suggests a technique to identify certain patient populations. Our model examines the patient population and clusters certain groups. Those subpopulations are then classified in terms of their appropriate medical treatment. As a result, we show the value of applying a DM model to more easily identify patients
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Due to the vast improvement in IT sectors ,the popularity health care organization conserve there da...
There are large quantities of information about patients and their medical conditions. The discovery...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
The exponential growth of health data necessitates the development of new methods that can handle ma...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Healthcare service centres equipped with electronic health systems have improved their resources as ...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Abstract—Since in health care systems the amount of data is continuously growing, data mining techni...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Due to the vast improvement in IT sectors ,the popularity health care organization conserve there da...
There are large quantities of information about patients and their medical conditions. The discovery...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
The exponential growth of health data necessitates the development of new methods that can handle ma...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools ...
Healthcare service centres equipped with electronic health systems have improved their resources as ...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Abstract—Since in health care systems the amount of data is continuously growing, data mining techni...
Health care industry produces enormous quantity of data that clutches complex information relating t...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Due to the vast improvement in IT sectors ,the popularity health care organization conserve there da...
There are large quantities of information about patients and their medical conditions. The discovery...