Einstein Prediction Builder Live Demo – Hospitalisation Likelihood

Case Study: Assessing the Likelihood of Hospitalisation

Predictive Model: We have engineered an advanced predictive system using Einstein Prediction Builder. This system is designed to estimate patient’s likelihood of hospital admission based on their current medical conditions.

Incorporated Factors: The model takes into consideration a variety of parameters, including:

• Patient’s medical history
• Past medication regimens
• Other relevant health information

Personalised Predictions: The system uses these factors to generate individualised predictions, enabling healthcare providers to make more informed decisions.

Demonstration Video: This demo video offers a comprehensive overview of how the system operates in real-time scenarios, specifically focusing on its utility for patients with fever symptoms.

Further Reading

• Einstein Prediction Builder Official Salesforce Documentation – https://help.salesforce.com/s/articleView?id=sf.custom_ai_prediction_builder_lm.htm&type=5
• Trailhead – https://trailhead.salesforce.com/content/learn/projects/prediction_builder