Table of Contents
Executive Summary 3
Facts about Alzheimer’s: 3
Usage of Data analytics in the healthcare sector 3
Internal Processes 4
1. Clinical Trials 4
2. Systems Biology 4
3. Simulation of processes: 4
4. Better disease prediction: 4
5. Risk and compliance management: 4
External Processes 4
1. Real-time health tracking 4
2. Electronic health records and Electronic medical records 4
3. Cross-selling applications 5
4. Credit services to medical practitioners 5
Internal Process – Clinical Trials 5
Applications 5
Competitive advantage 6
Metrics 6
Tools 7
Issues 7
External Process 8
Driving New Insights through Big Data Analysis 8
Usage of Unstructured and Structured Data 8
What’s in the AMP-AD Knowledge Portal? 8
Tools for Predictive Analysis 9
Recommendations 9
References 9 …show more content…
Firstly, None of the models say anything of the increasing risks of death among people suffering since they are mainly old. Secondly, the models developed till now use short follow-up periods and have potential predictors with limited range. Hence these studies have not identified the all the ranges of predictors for the disease. (Predicting Alzheimer's risk: why and how?, 2011) Prediction of Alzheimer’s disease is relatively a new field of study; none of the approaches developed till now have more than moderate level of accuracy. Hence they are not ready for widespread clinical use, however according to the prediction analysis Alzheimer’s is noted in people with a broad decline in health.
Tools for Predictive Analysis
• SAS Predictive Analytics
• IBM Predictive
Executive Summary 3
Facts about Alzheimer’s: 3
Usage of Data analytics in the healthcare sector 3
Internal Processes 4
1. Clinical Trials 4
2. Systems Biology 4
3. Simulation of processes: 4
4. Better disease prediction: 4
5. Risk and compliance management: 4
External Processes 4
1. Real-time health tracking 4
2. Electronic health records and Electronic medical records 4
3. Cross-selling applications 5
4. Credit services to medical practitioners 5
Internal Process – Clinical Trials 5
Applications 5
Competitive advantage 6
Metrics 6
Tools 7
Issues 7
External Process 8
Driving New Insights through Big Data Analysis 8
Usage of Unstructured and Structured Data 8
What’s in the AMP-AD Knowledge Portal? 8
Tools for Predictive Analysis 9
Recommendations 9
References 9 …show more content…
Firstly, None of the models say anything of the increasing risks of death among people suffering since they are mainly old. Secondly, the models developed till now use short follow-up periods and have potential predictors with limited range. Hence these studies have not identified the all the ranges of predictors for the disease. (Predicting Alzheimer's risk: why and how?, 2011) Prediction of Alzheimer’s disease is relatively a new field of study; none of the approaches developed till now have more than moderate level of accuracy. Hence they are not ready for widespread clinical use, however according to the prediction analysis Alzheimer’s is noted in people with a broad decline in health.
Tools for Predictive Analysis
• SAS Predictive Analytics
• IBM Predictive