Healthcare Data Analytics and Privacy Preservation by DCNN Algorithm

Data has become an integral part of the digital world with the advancement in computing technologies. The collection of data is very crucial with regards to data analytics. Every industry makes use of data analytics ranging from financial to other commercial applications but it becomes even more important in healthcare domain for the analysis of healthcare data. The present research work is mainly focused on classification/prediction problems of healthcare data based on deep learning (supervised) approaches using data mining techniques. There is a need to design an intelligent model (based on deep learning) which can classify the amount of data that is stored in our databases. Human data analytical capability rate is much smaller when compared to the amount of data that is stored. This (classification) becomes even more critical when it comes to healthcare data as it can help to detect, diagnose and treat the patients based on these classified data. The main goal of the thesis is to develop a deep learning-based model for classification tasks and the introduced DDS can be used in healthcare domain to improve the diagnostic speed, accuracy and reliability.