More than a year since they announced a partnership to advance machine learning advancement in areas such as oncology, precision medicine and imaging, the researchers of the Pittsburgh Health Data Alliance and AWS, are unveiling new AI-based techniques to assess breast cancer risk, understand tumor growth and better spot markers of depression. In one project, a team in the radiology department at University of Pittsburgh are using deep-learning systems to analyze mammograms in order to predict the short‐term risk of developing breast cancer and develop a more personalized approach for patients undergoing screening. Researchers gathered more than 450 de-identified normal screening mammogram images from 226 patients, half of whom later developed breast cancer and half of whom did not. With help from AWS tools, they developed two different machine learning models to analyze the images for characteristics that could help predict breast cancer risk. Both outperformed the simple measure of breast density, which today is the primary imaging marker for breast cancer risk.

Thanks to a Machine Learning Research Award from Amazon Web Services (AWS) to a research alliance supported by UPMC Enterprises, a seed has been planted to accelerate the consortium's medical research initiatives, help participating entrepreneurs more rapidly scale their innovations, and, in some small fashion, contribute to positioning the Pittsburgh area as a healthcare technology innovation hub. The award provides researchers access to Amazon's cloud-based platform and machine learning tools, enabling them to incorporate sophisticated technology into innovations at an early stage of the development process. These innovations "will be able to be deployed more easily in the real world," says Rob Hartman, PhD, director of translational science, UPMC Enterprises. The Amazon award was made to the Pittsburgh Health Data Alliance (PHDA), which was formed four years ago by UPMC, the University of Pittsburgh, and Carnegie Mellon University. PDHA uses "big data" generated in health care--including patient information in the electronic health record, diagnostic imaging, prescriptions, genomic profiles, and insurance records--to transform the way that diseases are treated and prevented, and to better engage patients in their own care, according to a news release.

Pittsburgh Health Data Alliance (PHDA) announced today that it is working closely with Amazon Web Services (AWS), an Amazon.com A unique consortium formed four years ago by UPMC, the University of Pittsburgh and Carnegie Mellon University (CMU), the PHDA uses the "big data" generated in health care -- including patient information in the electronic health record, diagnostic imaging, prescriptions, genomic profiles and insurance records -- to transform the way that diseases are treated and prevented, and to better engage patients in their own care. New machine learning technologies and advances in computing power, like those offered by 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. Through the AWS Machine Learning Research sponsorship, PHDA scientists from both Pitt and CMU expect to accelerate research and product commercialization efforts across eight projects, including those with the potential to create an individual risk score for every cancer patient, thus enabling doctors to better predict the course of a person's disease and response to treatment; use 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. Data are secure, anonymized and stay with PHDA institutions.