- Objective
As most of the Health care organizations have automated their back end operations through information systems. Clinical trail data is growing exponentially and it is becoming voluminous and heterogeneous. Health care data mining provides plethora of opportunities for hidden pattern investigation from these data sets. These knowledge discovery can be used by physicians to determine diagnosis and treatment for patients in health care organization.
Usage of Data mining can enable health care organization to determine the trends in patient conditions and early identification of contagious diseases which can be accomplished by data analysis from different perspectives and identifying relations and patterns from unrelated information.
Having said that , cognitive learning will enable the healthcare industry in India to reach immicable population easily. 2. Scope
This tool will build a predictive model for chronic kidney disease, diabetes and time series forecasting of Malaria.
Generate Decision Tree Exploratory Data Analysis. Regression Analysis Cluster Analysis Time series analysis and forecasting of Malaria information
Out of Scope:
Naïve Bayesian classification and support vector machine are out of scope.
Software Requirement Specification 2.1 Functional Requirements Various combinations of the functional requirements are covered in the below three use case scenarios -
System should generate predictive model for determining the risk of developing a chronic key disease based on mined health data.
Inputs: Data collected from hospitals for 2 months of period available in UCI machine learning https://archive.ics.uci.edu/ml/datasets/Chronic_Kidney_Disease
Outputs:
Build a classifier model for above scenario to predict the future patient symptoms for CKD. Perform Exploratory data analysis. Cluster analysis of Clinical data to discover patterns