1. Collection of relavant datasets (mixture of general inpatient and cardiac related data)

2. Data storage to be done on public cloud

3. Application of a new classification mechanism of machine learning identifying the drawbacks of previous existing classification techniques and designing a new one which solves or overcome the drawback of previous techniques to label all the cardiac related data based on its extent of severity

4. Application of a new clustering mechanism of machine learning to group the cardiac data based on relevant parameters identified as part of feature selection,creating clusters.

5. Generating a new predictive modelling for all the observed data and showing the prediction results( Here application of R programming)

6. Application of cognitive computing on the same data and show a comparision for both simulations of predictive modelling and cognitive computing and show that cognitive computing yields far better results.


1. Justification of the title

2. Research in the concerned area.

3. Limitations and Future Enhancements in the concerned area.

4.A survey paper in a reputed journal like IEEE,ACM,SPRINGER etc specifying the literature survey of the ongoing research of the concerned area.

5. Preparation of the Data( Here our datasets gathered).

6. Existing and Proposed System and explanation of problem statement in detail

7. Architectural Framework of the Project.

8. Tools and techniques to be used in the Project.


1. Processing of the Datasets

2. Data cleaning, Filling up of the missing values using several mechanisms.

3. A new or ensembled mechanism used for classification of the required data.

4. A new or ensembled method of clustering

5. Mechanisms for feature selection.

6. Performing analytics on the organised data ( both collected data and online data).


1. Development of a new algorithm to design a prediction model.

2. Comparing the effectiveness of our applied techniques with the existing ones.

3. Measuring the efficiency and effectiveness of the obtained results with that of the real time.

4. Generating inreactive reports of the Analysis using tools like tableau,silk,Big sheets etc.

5. Generating necessary push up messages to the patient relations giving update status of the patient condition(Front end).


1. Upon completion of each stage need to publish the work completed in a reputed journal or conference ( SCI Journals).

2. Totally require 3 journals + one survey paper.

3. Upon acceptance of work from guide proceed for thesis writing

Skills: Data Mining, Data Science, Hadoop, Machine Learning (ML), R Programming Language

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About the Employer:
( 0 reviews ) Bangalore, India

Project ID: #18158554

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