Predictive Health Engine for Digital Health
Predict and diagnose disease
It’s no secret that patients have better health outcomes when you identify and treat diseases early. The problem is that the annual health checkup doesn’t help predict disease, and it rarely catches diseases in their early stages. The solution is to track patient lifestyle habits and biomarkers over time and use sophisticated machine learning (ML) algorithms to detect and predict diseases when they’re easier to treat.
A disease recognition analytics engine
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
