Patient Outcome Prediction

• Using Historical Patient data ML models can predict outcomes.
• Prediction about Readmission of patients with chronic conditions.

Disease Surveillance and Early Detection

• Early detection of diseases can happen based on data from various sources including social media and wearable devices.

Medical Imaging Analysis

• Computer vision and Deep Learning can be used to analyze images such as X-rays, MRIs and CT Scans for the early detection of conditions like cancer or fractures.

Drug Discovery and Development.

• Analyzing Biological data and clinical test results, drug discovery can be accelerated by identifying potential drug candidates.

Case Studies in Healthcare





IBM Watson for Oncology

• IBM Watson analyzes vast amount of medical literature, patient records and clinical trial data and provides treatment recommendations improving the speed and accuracy of cancer care.

Mount Sinai’s BioMe Biobank

• BioMe Biobank collects genetic and clinical data from thousands of patients and use this data to study the genetic basis of various diseases and develop personalized treatment plans.

GE Healthcare’s Imaging Analytics

• AI Powered platform that analyzes medical images to detect diseases like lung cancer, liver lesions and helps radiologists in making accurate diagnosis.

Google Health’s DeepMind and Moorfields Eye Hospital Partnership.

• Machine learning to detect early eye diseases especially age related macular degeneration and diabetic retinopathy.

Data Analytics usage in BFSI.

• Fraud detection and prevention: Data analytics can identify fraudulent activity, such as a bank flagging customers who make many small transactions quickly.
• Risk management: Data analytics assesses and manages business risk, such as a bank using data to approve loans.
• Customer segmentation and personalization: Data analytics segments customers based on needs and preferences, enabling targeted marketing and product development.
• Product development: Data analytics develops new products and services, such as insurance tailored to millennials.
• Operational efficiency: Data analytics identifies and eliminates inefficiencies, such as banks streamlining loan processing.

Case Studies in Banking





JP Morgan Chase –Fraud Detection

• Manage Risk and Detect Fraud.
• Analyze Vast amount of data to identify unusual patterns which might indicate fraudulent activities.
• Prevents Millions of dollar loss and maintain trust of customers.
• For Instance, if a customer suddenly makes an unusual high value transaction in a foreign country, the system can trigger an alert for further investigation.

Wells Fargo-Customer Segmentation.

• Uses Data Analytics to segment Customer base by analyzing transaction history, income levels and demographics.
• Create targeted marketing campaigns for different customer segments.
• Personalized marketing campaigns and Product recommendations.

HSBC- Anti Money Laundering.

• Analyze transactional data and customer profiles to identify suspicious patterns and potential money laundering activities.

Benefits of Data Analytics in Healthcare and BFSI.

The benefits of data analytics in healthcare and BFSI are numerous. By using data analytics, organizations can:
• Improve customer service
• Reduce costs
• Improve efficiency
• Make better business decisions
• Develop new products and services
• Reduce risk
• Improve Compliance

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