Application of data mining techniques to measure cancer morbidity and mortality data

By: Call Number: AIT RSPR no.ICT-17-03 Contributor(s): Material type: SeriesSeries: Asian Institute of Technology. Research studies project report ; no. ICT-17-03Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2017Description: 49 leaves : illSubject(s): Online resources: Dissertation note: Research Studies Project Report (M. Eng.) - Asian Institute of Technology, 2017 Summary: In this modern era cancer is one of the most common disease we are facing everywhere. The cancer rate is increasing enormously the data is huge to classify it we are using data mining techniques. In this report the data is collected from a cancer hospital, Hyderabad. The data is a combination of different cancers age and treatment and mortality. To estimate the statistics of cancer with respect to age, treatment and mortality we are using decision tree classification for classification of data.For performing decision tree we use rapid miner software to analyze the above statistics
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A research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Communication Technologies, School of Engineering and Technology

Research Studies Project Report (M. Eng.) - Asian Institute of Technology, 2017

In this modern era cancer is one of the most common disease we are facing everywhere. The cancer rate is increasing enormously the data is huge to classify it we are using data mining techniques. In this report the data is collected from a cancer hospital, Hyderabad. The data is a combination of different cancers age and treatment and mortality. To estimate the statistics of cancer with respect to age, treatment and mortality we are using decision tree classification for classification of data.For performing decision tree we use rapid miner software to analyze the above statistics

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