Health care is a data-rich industry, driven by rapidly evolving digital health technologies. Our AI-powered predictive analytics enable you to realize
the full value of your data.
Delivering Predictions in Healthcare
Therapeutic outcomes prediction. Population health. Patient care pathways. Disease progression. WorldQuant Predictive’s federated learning platform allows organizations to create and apply predictive solutions to a larger pool of data—yours, ours, and third-party data—without handing over proprietary assets. We enable our partners to strike the delicate balance between protecting both their data and patients’ privacy, while accessing collaborative model libraries to accelerate medical advances—benefiting patients, physicians, and society.
Predictive Healthcare Use Cases
Our proprietary clinical data and approach to predictive modeling lets us understand and simulate likely therapeutic outcomes based on multiple factors, e.g., patient cohort, disease progression, and treatment protocols.
Predictive analytics can impact the health of populations by improving risk stratification, discovering outcome correlations and enabling evidence-based strategies.
Through predictive factor analysis we can better understand and monitor disease progression as well as predict adverse events or side effects of treatment to provide patients with the right intervention at the right time.
Predictive Care Pathways
By improving our understanding of social determinants of health, we can generate actionable care pathways and identify the best potential outcomes for patients.
Working with our partners, we can create predictive models that help optimize care while reducing costs within a health network, democratizing provider services.
Proprietary Clinical and Claims Data Assets
Through partnerships and acquisitions, we have amassed a significant collection of healthcare data that includes clinical, claims, performance, and hospital operations data. We build predictive model libraries that are immediately available to our clients to backtest against their own proprietary data assets.