The partnership will leverage machine learning technology to advance research for the treatment and management of certain diseases.
The University of Texas Health Science Center at Houston (UTHealth), Amazon Web Services, Cardinal Health, and Virtusa Corporation are partnering to use machine learning to advance medical research.
The collaboration will initially focus on finding the best treatment and management strategies for subarachnoid hemorrhage (SAH) and diabetes based on healthcare data and computer simulation. Virtusa and Cardinal Health will simulate a comprehensive dataset made up of EHRs representing more than 30,000 patients.
“We are developing novel statistical methods and machine learning approaches to interrogate EHR databases to identify the best treatment strategies and risk factors for a variety of diseases using real-world evidence,” said UTHealth faculty member Hulin Wu, PhD, the Betty Wheless Trotter Professor and chair of the department.
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“The EHR data simulated by Virtusa’s platform will help us test and validate our new predictive models and machine learning algorithms before applying to the real EHR data.”
Virtusa will use a cloud-based platform consisting of a comprehensive HIPAA-compliant data lake with multiple data sources, pre-built APIs, and AI and machine learning models to help researchers uncover hidden trends and better treat a range of medical conditions.
“Life science companies must address how to seize the upside of disruption in today’s transformation age. Future value in life science is driven by innovation that focuses on outcomes with a high degree of personalization and is fueled by unlocking the power of simulated data,” said Anthony Lange, senior vice president, Life Sciences, Virtusa.
“At Virtusa, we recognize the critical importance of collaboration in advancing AI technologies to create intelligent solutions that make lives better and businesses more efficient. As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions.”
UTHealth will use the simulated data from Virtusa and Cardinal Health to train and develop machine learning models capable of predicting treatment outcomes for certain types of illnesses. The data provided through Cardinal Health’s Proxi patient population simulation requires minimum data cleaning and preparation.
“Cardinal Health is excited to see another effective use for Proxi, our simulated EHR data platform,” said Jeff Graham, principal, Big Data Analytics, Cardinal Health. “Through the use of our technology, organizations like UTHealth can work with simulated clinical records to accelerate research, augment existing real-world-evidence, and save time by using clean, ready-to-use linked data.”
More than 20 faculty and students in the Department of Biostatistics and Data Science at UTHealth School of Public Health will team with clinicians, epidemiologists, and computer scientists for the machine learning project.
“With all the hype associated with Big Data, it has been exceptionally satisfying to work in close collaboration with our partners at Virtusa, Cardinal Health, and now UTHealth to develop innovative, effective solutions in the AI technology space that has the potential to impact human health,” said Daniel H. Robertson, PhD, research fellow and vice president of digital technology, Indiana Biosciences Research Institute (IBRI), which serves as a consultant to Virtusa on issues of molecular biology in engagements, including this one with UTHealth.
The new partnership will aim to advance disease treatment and management with innovative technologies.
“The availability of Virtusa’s Machine Learning Model Packages for disease state classifications on AWS Marketplace will assist our health care data scientist customers to deploy and integrate machine learning models into their applications quickly,” said Ananth Balasubramanian, global lead of Healthcare and Life Sciences, AWS Marketplace, Amazon Web Services, Inc.
“We are excited to have another set of great solutions added to the catalog to help our customers harness the power of AWS to build mission-critical applications.”
Source: Health IT Analytics