The Pittsburgh Health Data Alliance (PHDA) has announced a machine learning research sponsorship from Amazon Web Services (AWS) that would see the alliance aim to advance innovation in areas such as cancer diagnostics, precision medicine, voice-enabled technologies, and medical imaging.
The PHDA is a consortium formed by Pittsburgh's UPMC hospital, the University of Pittsburgh, and Carnegie Mellon University.
The alliance focuses on the data generated in healthcare, such as patient information in electronic health records, diagnostic imaging, prescriptions, genomic profiles, and insurance records, and is charged with using that data to transform the way diseases are treated and prevented, as well as to better engage patients in their own care.
The PHDA said new machine learning technologies and advances in computing power, such as Amazon SageMaker and Amazon EC2, are making it possible to "rapidly translate insights discovered in the lab into treatments and services that could dramatically improve human health".
PHDA scientists from both universities are expected to accelerate research and product commercialization efforts across eight projects through the AWS sponsorship, such as those with the potential to create an individual risk score for every cancer patient.
The ability to create an individual risk score for cancer patients, the alliance said, could enable doctors to better predict the course of a person's disease and response to treatment.
Other projects the PHDA will undertake as part of the AWS deal include the use of a patient's verbal and visual cues to diagnose and treat mental health symptoms, and reduce medical diagnostic errors by mining all the data in a patient's medical record.
Associate dean for research at Pitt's Swanson School of Engineering and the John A. Swanson Professor of Bioengineering David Vorp and his team are using AWS resources to improve the diagnosis and treatment of abdominal aortic aneurysms, which the alliance said is the 13th-leading cause of death in western countries.
"Currently, clinicians can use only the simple measurements of an aneurysm's diameter and growth rate to predict the risk of a rupture," the PHDA said.
"With the latest advances in machine learning, we are developing an algorithm that will provide clinicians with an objective, predictive tool to guide surgical interventions before symptoms appear, improving patient outcomes," Vorp added.
Similarly, a CMU team led by professor of biological sciences and computational biology Russell Schwartz and Jian Ma will use AWS support to develop algorithms and software tools to better understand the origin and evolution of tumor cells.
According to the PHDA, the CMU project will use machine learning to gain insights into how tumors develop and to predict how they are likely to change and grow in the future.
See also: The 10 most popular machine learning frameworks used by data scientists (TechRepublic)
"Data-driven, genomic methods guided by an understanding of cancers as evolutionary systems have relevance to numerous aspects of clinical cancer care," Schwartz explained.
"These include determining which precancerous lesions are likely to become cancers, which cancers have a good or bad prognosis, and which of those with bad prognoses might respond long-term to specific therapies."
"We believe that machine learning can significantly accelerate the progress of medical research and help translate those advances into treatments and improved experiences for patients," AWS vice president of machine learning Swami Sivasubramanian added.
"We are excited to bring our machine learning services and cloud computing resources to support the high-impact work being done at the PHDA."
UPMC Enterprises, which funds the PHDA and focuses on commercializing its research, expects AWS machine learning and artificial intelligence services will help Pittsburgh become the premier hub of technology innovation in healthcare.
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