Institute for Cyber and Data Sciences seed grants spur technological innovation
Penn State Institute for Computational and Data Sciences provides seed funding for faculty projects that advance computation-enabled and data-enabled research. Grants are awarded annually and provide an allotment of time for ICDS’s Research Innovations with Scientists and Engineers (RISE) team to provide a research team with their expertise in computational science.
“Seed grants from ICDS help our faculty explore novel ideas in applying machine learning and informatics to biomedical and health science challenges,” said Dr. Leslie Parent, vice dean for research and graduate studies. “These projects support the College’s strategic plan goal of harnessing artificial intelligence and big data to make rapid advances in biomedical research and health care.”
The Institute recently awarded seed grants to eight Penn State researchers – including one to Dr. Carrie Daymont, associate professor of pediatrics and public health sciences at Penn State College of Medicine. She uses data from electronic health records to study atypical growth in children. Errors in weight, height and head circumference data in electronic health records make studying these large datasets difficult. Daymont’s focus on studying children with atypical growth makes excluding outlying measurements from the data inappropriate.
Daymont developed the software application, growthcleanr, to “clean” pediatric height and weight information from electronic health records, excluding data points that are implausible for an individual child, to make it easier for her and other researchers to work with the data. She also developed a similar tool for adult height and weight data in collaboration with the Centers for Disease Control and Prevention.
“My ultimate goal is to make this tool more accessible to other clinical researchers,” Daymont said. “The RISE seed grant has helped me develop cross-campus relationships with people who will help further develop and enhance the software.”
Daymont and the RISE team will make the software available on the Comprehensive R Archival Network, which will allow it to be used by a wider swath of researchers for future studies. They will also use tools to generate large synthetic datasets to test the modified software.
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