The center for computational health (ComputeHealth) at Georgia Tech is formed to revolutionize healthcare research and delivery through computational methods and big data systems. 

The ComputeHealth center has three key goals:

  • The creation and adoption of standardized open source platforms for health analytics, so that industrial players can target application layers, not infrastructure, and integration with clinical systems and diverse data sources can be performed at a few points of contact rather than many.
  • The creation of a health big data ecosystem which includes all major stakeholders, including providers, payers, pharma, government, industry, and the research community. Unification around platforms and standards for data analytics can facilitate this convergence.
  • The development of gold standard analytic methods and best practices for data acquisition and management in addressing the challenges and opportunities in exploiting diverse multimodal data sources for health applications.

Platform: Biomedical Analytic Software and Ecosystem (BASE)

Big data health applications require the following three categories of capabilities which are not provided by existing systems:

  • Health applications require a specific analytics stack which supports core capabilities in prediction, phenotyping, and disease progression.
  • Issues surrounding data ownership, privacy, and access control are ubiquitous big data concerns, but health applications create unique challenges due to legal and ethical considerations. Two specific issues are insuring that individuals can access and control the use of their data and ensuring that datasets can be federated for analysis while remaining physically distributed.
  • Health data is inherently multimodal, encompassing clinical, behavioral, and –omics data types. The long term promise of health big data is to leverage these complementary data sources, and this in turn will require specialized data models and integration methods that are likely to cut across multiple categories of disease.

Industry Consortium

The BASE platform will catalyze the development of a health analytics ecosystem

  • Providers – This sector is interested in quality metrics, with a focus on adverse event detection, outcome prediction, demand forecasting and personalized care protocol design. 
  • Payors – This sector is concerned with cost metrics, and focuses on prediction of claims fraud, utilization prediction, and readmission prediction. 
  • Pharmaceuticals – This sector focuses primarily on personalized treatment selection and the design and efficient implementation of clinical trials, along with discovery science. 
  • Government – This sector has broad interests, from biosurveillance to policy and large scale initiatives such as the recent Precision Medicine Initiative. 
  • Technology – This sector’s interests range from EHR systems through electronic health record vendors, cloud providers and device technologies. 

Computational Methods

ComputeHealth center is led by Georgia Tech faculty from college of computing, college of engineering and college of science. Many novel computational methods have been developed by our team includes: computational phenotyping, behavioral imaging, genomic analysis, bioinformatics, device and sensor design. 

 

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  • September 30, 2015
    Georgia Tech center of computational health is formed! via @computehealth

Platform: Biomedical Analytic Software and Ecosystem (BASE)

Industry Consortium

Computational Methods