SURVIVAL PREDICTING OF ORAL AND PHARYNGEAL CANCER USING MACHINE LEARNING TECHNIQUES(SQL FOR PREPROCESSING AND WEKA FOR ANALYSIS. I AM ATTACHING A SAMPLE TO GIVE YOU AN IDEA. You are not predicting survival rate, but survival. Rate exists in population and there is nothing to be predicted. What you want is a model that will take data for one individual and output the chance of survival. You will be required to submit this project in 3 portions: You need to find data from SEER or MIMIC that is suitable to solve the problem. You may want to use only newer data (after 2004 or newer). You need to decide based on variable availability and sample size. Most importantly the data need to be on the right level of aggregation. Start exploring SEER data or MIMIC to see how to use their software to download, etc. The project report should include, but be not limited to: Direct application of existing software to publicly available datasets is not sufficient. The projects must demonstrate significant efforts in data manipulation, processing, and mining. Projects must also illustrate understanding of applied techniques as well as the healthcare problem addressed. Requirements: 12 Report Presentation Source code, results, materials, findings problem description data selection data pre-processing selection DM methods application of methods analysis of results review of available literature and related work conclusions and description of the impact on healthcare Report
Presentation
Source code, results, materials, findings problem description
data selection
data pre-processing
selection DM methods
application of methods
analysis of results
review of available literature and related work
conclusions and description of the impact on healthcare
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