Emerging Innovations

We are serious about getting AI innovations to the bedside. The emerging innovations listed below have completed initial testing and proof-of-concept validation. Research projects that make it to the emerging innovation stage have high confidence for commercial viability and will be ready to license in 1-2 years.

Companies interested in sponsoring further R&D can option for right of first refusal! Explore our innovations below and connect with U-M Innovation Partnerships to learn more!

Featured

Causal Hospital reAdmission Risk Prediction (C-HARP)

C-HARP predicts the likelihood that patients will benefit from Transitions of Care (TOC) interventions.

Hospital Readmissions Risk Prediction and Prevention (HARPP)

The HARPP model predicts risk of readmission and the likelihood of a patient benefiting from a post discharge intervention.

Data-Driven Interventions for Reducing C. Difficile Incidence

This AI model uses predictions to identify patients most at risk for C. Diff infection.

PICTURE: Pediatric General Floor Deterioration Prediction

PICTURE is a suite of machine learning algorithms that utilizes electronic health record (EHR) data to predict patient deterioration in hospital settings. This iteration is modeled specifically for adult inpatients in a general floor.

Ambulatory Surgery Center Model

This predictive model that will automatically assign patient locations for a majority of cases.

PICTURE: Adult General Floor Deterioration Prediction

Emerging Innovations

Emerging Innovations

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