Predictive Health Engine for Digital Health

Researchers aren’t the only ones who can identify patterns in patient data. Mahalo’s predictive health engine combines machine learning with rules-based algorithms to identify diseases and recommend treatment plans. Our engine is like a research assistant that compares patient health data logged on the Mahalo Unified Data Platform with patient population data for other patients who contracted a disease. The engine hunts for patterns and creates models for predicting and diagnosing specific health conditions.

Start with known health outcomes

• Use your existing data from studies or digital therapies
• Identify patients whom clinicians diagnosed with a disease
• Add disease progression data when available
• Create a second patient population who don’t have the disease
  

Generate detection and prediction models

• Use positive and negative patient cases
• Control for false positive and negative cases
• Run algorithms on patients not part of the training set
• Confirm accuracy with clinic visits for disease screening
• Repeat as needed to increase accuracy
  

Faster to production than R

• R is good for developing models
• You can't build production ML applications with R
• Design and run production models in one place with Mahalo
• Get to market faster with our Predictive Health Engine
• Collect, model, and analyze data on one platform