Challenge Winners

Stage 2 Finalists

Congratulations to the seven finalists who will advance to the final round of the Artificial Intelligence (AI) Health Outcomes Challenge!

Participant: Ann Arbor Algorithms Inc. 
Proposed Solution: Generalizing Time-to-event Algorithms to Deep Learning-based Prediction for CMS Data
Geographic Location: Sterling Heights, Michigan

Participant: Deloitte Consulting LLP 
Proposed Solution: Further, Faster: The Deloitte Team’s Approach to Harnessing the Power of AI to Improve Health Outcomes
Geographic Location: Arlington, Virginia

Participant: Jefferson Health 
Proposed Solution: Using AI to Improve Medicare Population Health, Optimize Ambulatory Scheduling, and Reduce Adverse Events at Hospitals
Geographic Location: Philadelphia, Pennsylvania

Participant: University of Virginia Health System 
Proposed Solution: Actionable AI
Geographic Location: Charlottesville, Virginia

 

 

 

Participant: ClosedLoop.ai 
Proposed Solution: Healthcare’s Data Science Platform
Geographic Location: Austin, Texas

Participant: Geisinger 
Proposed Solution: Reducing Adverse Events and Avoidable Hospital Readmissions by Empowering Clinicians and Patients
Geographic Location: Danville, Pennsylvania

Participant: Mathematica Policy Research, Inc. 
Proposed Solution: The CPC+ AI Model by Mathematica
Geographic Location: Princeton, New Jersey

 

Stage 1 Finalists

The 25 Participants, titles of proposed solutions and geographic locations are listed below:

Participant: Accenture Federal Services
Proposed Solution: Accenture Federal Services AI Challenge
Geographic Location: Arlington, Virginia

Participant: Ann Arbor Algorithms Inc.
Proposed Solution: Generalizing Time-to-event Algorithms to Deep Learning-based Prediction for CMS Data
Geographic Location: Sterling Heights, Michigan

Participant: Booz Allen Hamilton
Proposed Solution: Booz Allen Launch Stage Submission
Geographic Location: McLean, Virginia

Participant: ClosedLoop.ai
Proposed Solution: Healthcare’s Data Science Platform
Geographic Location: Austin, Texas

Participant: Columbia University Department of Biomedical Informatics
Proposed Solution: The CLinically Explainable Actionable Risk (CLEAR) Model from Columbia University Department of Biomedical Informatics
Geographic Location: New York, New York

Participant: CORMAC
Proposed Solution: CORMAC Response to Challenge Questions
Geographic Location: Columbia, Maryland

Participant: Deloitte Consulting LLP
Proposed Solution: Further, Faster: The Deloitte Team’s Approach to Harnessing the Power of AI to Improve Health Outcomes
Geographic Location: Arlington, Virginia

Participant: Geisinger
Proposed Solution: Reducing Adverse Events and Avoidable Hospital Readmissions by Empowering Clinicians and Patients
Geographic Location: Danville, Pennsylvania

Participant: Health Data Analytics Institute
Proposed Solution: HDAI’s Analytic Platform Technology for Healthcare Improvement
Geographic Location: Dedham, Massachusetts

Participant: HealthEC, LLC
Proposed Solution: Leveraging Artificial Intelligence to Predict and Improve Health Outcomes, Maximize Quality Improvement, and Reduce Costs
Geographic Location: Edison, New Jersey

Participant: Hospital of the University of Pennsylvania
Proposed Solution: The Intelligent Risk Project
Geographic Location: Philadelphia, Pennsylvania

Participant: IBM Corporation
Proposed Solution: AI for Explainable Adverse Event Prediction: Empowering Beneficiaries and Providers to Improve Health Outcomes
Geographic Location: Yorktown, New York

Participant: Innovative Decisions Inc. (IDI)
Proposed Solution: Multi-Modeling with Augmented Datasets for Positive Health Outcomes (MADPHO)
Geographic Location: Vienna, Virginia

 

 

 

Participant: Jefferson Health
Proposed Solution: Using AI to Improve Medicare Population Health, Optimize Ambulatory Scheduling, and Reduce Adverse Events at Hospitals
Geographic Location: Philadelphia, Pennsylvania

Participant: KenSci Inc.
Proposed Solution: Assistive Intelligence for Unplanned Admissions and Adverse Events Prediction
Geographic Location: Seattle, Washington

Participant: Lightbeam Health Solutions, LLC
Proposed Solution: AI Risk Predictions- preventing hospital, ER and SNF admissions
Geographic Location: Irving, Texas

Participant: Mathematica Policy Research, Inc.
Proposed Solution: The CPC+ AI Model by Mathematica
Geographic Location: Princeton, New Jersey

Participant: Mayo Clinic
Proposed Solution: Claims-based Learning Framework (CBLF)
Geographic Location: Rochester, Minnesota

Participant: Mederrata
Proposed Solution: Boosting medical error and readmission prediction by leveraging Deep Learning, Topological Data Analysis, and Bayesian modeling
Geographic Location: Columbus, Ohio

Participant: Merck & Co., Inc.
Proposed Solution: Actionable AI to Prevent Unplanned Admissions and Adverse Events
Geographic Location: Kenilworth, New Jersey

Participant: North Carolina State University (NCSU)
Proposed Solution: Multi-Layered Feature Selection and Dynamic Personalized Scoring
Geographic Location: Raleigh, North Carolina

Participant: Northrop Grumman Systems Corporation (NGSC)
Proposed Solution: Reducing Patient Risk through Actionable Artificial Intelligence: AI Risk Avoidance System (ARAS)
Geographic Location: Herndon, Virginia

Participant: Northwestern Medicine
Proposed Solution: A human-machine solution to enhance delivery of relationship-oriented care
Geographic Location: Chicago, Illinois

Participant: Observational Health Data Sciences and Informatics (OHDSI)
Proposed Solution: OHDSI Submission
Geographic Location: New York, New York

Participant: University of Virginia Health System
Proposed Solution: Actionable AI
Geographic Location: Charlottesville, Virginia

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