Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools provide a useful for alternative framework that addresses this problem. This study follows a DM technique to identify diabetic patients. We develop a model that clusters diabetes patients of a large healthcare company into different subpopulation. Consequently, we show the value of applying a DM model to identify diabetic patients. Keywords
Data mining is a process of extracting information from a dataset and transform it into understandab...
Background: Diabetes mellitus (DM) is one of the most common diseases in the world. Complications of...
Introduction: Nowadays, diabetic disease is one of the most common, dangerous and costly diseases in...
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 ...
Data mining is the process of selecting, exploring, and modeling large amounts of data to discover u...
Data mining techniques explore critical information in various domains (for example in CRM (customer...
Data mining is the process of selecting, exploring, and modeling large amounts of data to discover u...
Introduction: The Health Industry companies store a vast amount of data in order to support administ...
The accumulating amounts of data are making traditional analysis methods impractical. Novel tools em...
Abstract: Data mining is the process of analyzing data from different perspectives and summarizing i...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Data mining plays an important part in the healthcare sector disease prediction. Techniques of data ...
Data mining is a process of extracting information from a dataset and transform it into understandab...
Background: Diabetes mellitus (DM) is one of the most common diseases in the world. Complications of...
Introduction: Nowadays, diabetic disease is one of the most common, dangerous and costly diseases in...
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 ...
Data mining is the process of selecting, exploring, and modeling large amounts of data to discover u...
Data mining techniques explore critical information in various domains (for example in CRM (customer...
Data mining is the process of selecting, exploring, and modeling large amounts of data to discover u...
Introduction: The Health Industry companies store a vast amount of data in order to support administ...
The accumulating amounts of data are making traditional analysis methods impractical. Novel tools em...
Abstract: Data mining is the process of analyzing data from different perspectives and summarizing i...
Health care data collections are usually characterized by an inherent sparseness due to a large card...
Data mining plays an important part in the healthcare sector disease prediction. Techniques of data ...
Data mining is a process of extracting information from a dataset and transform it into understandab...
Background: Diabetes mellitus (DM) is one of the most common diseases in the world. Complications of...
Introduction: Nowadays, diabetic disease is one of the most common, dangerous and costly diseases in...