We recently welcomed several new faculty members:

Kevin Dufendach, MD: Neonatologist/Researcher Brings User-Centered Design to Clinical Tools

Kevin Dufendach, MD, is combining his interests in user-centered design, electronic health records and neonatology to improve the way clinicians interact with software. He is a clinician in the Divisions of Neonatology and Pulmonary Medicine and a researcher in the Division of Biomedical Informatics, where he explores ways to design smarter. Medical software can be a big asset to clinicians, allowing them to streamline data management and care for patients with greater precision. But design is everything—if the software doesn't meet clinicians' unique needs, it could become more of a hindrance than a help. Dufendach developed an open-source tool called VandAID that gives users a quick and easy way to manipulate an interactive canvas to select the colors, layouts, fonts, and other design choices so they can more easily communicate their preferences to developers. He is already applying this tool to a variety of care and research challenges, including collecting patient feedback for a genetic research project and developing a neonatal-specific inpatient portal that will make it easier for parents and NICU staff to communicate effectively.

Emily Miraldi, PhD: Immuno-Engineering from the Numbers

Emily Miraldi, PhD, is a computational and systems biologist with the Divisions of Immunobiology and Biomedical Informatics. Coming from New York University and the Simons Foundation, the MIT-trained scientist focuses on immuno-engineering: Altering the behavior of specific immune cell populations during disease without compromising the body’s normal immune function. Her team is helping develop more precise therapies to ramp up immune cells and battle cancer, or turn them down to prevent autoimmune disease, while not interfering with healthy immune function. Genomics technologies provide high-dimensional snapshots of the cellular molecules (DNA, RNA, proteins, metabolites) that drive cell behavior. Mathematical modeling can stitch these snapshots together into a blueprint of how combinations of molecules work together to orchestrate responses. Miraldi and her colleagues use these models to predict the effect of molecular interventions (genetic, diet, drugs) on individual cell types. Learn more.

Yizhao Ni, PhD: Harnessing Artificial Intelligence to Support Clinical Decision Making

Yizhao Ni, PhD, focuses his research on the development of machine learning, natural language processing and information retrieval techniques to support clinical decision making. His research is application-oriented, aiming to improve the quality of health care in terms of efficiency, effectiveness and safety by providing more effective provisioning of useful data; helping clinicians generate more objective clinical decisions; and providing more reliable proactive prediction of clinical outcomes. His collaborators include clinical providers, information service administrators and biomedical and computational scientists. He helped develop an automated algorithm that shows promise in improving medication safety within the pediatric environment by reducing manual discrepancies for patients discharged from the hospital. He collaborated with Drew H. Barzman, MD, on a project to develop a standardized, sensitive and rapid method to identify students at high risk for physical aggression and violence toward others at schools. He also developed a novel real-time computerized system that collects and processes information from several electronic health record sources simultaneously to monitor medication administration accuracy, rapidly alerting providers to correct any errors. In addition to his research, Dr. Ni is serving as a machine learning specialist in multiple quality improvement projects at Cincinnati Children's.

Surya Prasath, MD: Bringing Imaging Informatics Expertise to Cincinnati Childrens

Surya Prasath, PhD, is an expert in imaging informatics, image processing and computer vision. His main lines of research are in mathematical analysis and image processing for various biomedical imagery modalities. He has worked with imagery ranging from micro-microscopy and histopathology to macro-MRI and endoscopy. Previously with the University of Missouri-Columbia, he joined the Division of Biomedical Informatics in 2018. He is working on a large-scale histopathological image analysis of brain tumors utilizing data sets from the National Cancer Institute and Cincinnati Children’s. He aims to develop automatic biomedical image analysis tools, emphasizing the integration of imaging informatics data with clinical, genetic and genomic information for precision medicine and research. One focus will be on designing and developing software for processing large-scale spatiotemporal biomedical data sets in an effective and clinically meaningful way. He also aims to create and enhance data mining tools with integrated image analysis modules and high-performance computations.

Krishna Roskin, PhD: Using Computational Biology to Unlock Human Immune System Secrets

Krishna Roskin, PhD, an informaticist and immunobiologist at Cincinnati Children’s, is pairing computational methods with immunobiology to improve our understanding of the human immune system. One of his big ideas is to aggregate immune system data into an atlas to serve as a reference. He is working to create an antibody dictionary that associates antibodies with their antigens, which could allow healthcare providers to analyze the blood sample of a person with an unknown infection to make a diagnosis or look for signs of past antigen exposure. Such a dictionary would also be useful in reverse engineering vaccines. He aims to be a bridge between immunology and informatics. Roskin began his studies at the University of California Santa Cruz where the first completed draft of the human genome and mammalian comparative genomics, in the form of the mouse and rat genome projects, was being born. His work centered on analyzing the mouse genome and comparing it to the human genome. He is now applying the computational skills and insights he gained from full genome comparative analysis to sequence-based immune monitoring.

Mayur Sarangdhar, PhD: Unraveling the Causes and Mechanisms of Drug Toxicity

Mayur Sarangdhar, PhD, is a bioinformatics-trained computational scientist who focuses on integrating high-dimensional computational approaches with systems biology knowledgebases. Sarangdhar developed a novel platform, AERSMine, to mine the clinical responses of millions of patients to all FDA-approved drugs in order to identify unexpected clinical harm, benefits and alternative treatment choices for individual patients. The database has the potential to help reduce negative side effects from prescription drugs and identify opportunities to reposition existing drugs for new uses. The tool allows anyone from physicians to the general public to rapidly find, combine and analyze the growing volume of drug information stored in the U.S. Food and Drug Administration’s Adverse Reporting System (FAERS). Sarangdhar is also a member of the Children’s Oncology Group and is leading the effort to delineate differential treatment- and age-specific toxicity profiles within pediatric and young adult cancer patients across multiple studies and disease groups. Learn more about Dr. Sarangdhar's previous research.

Danny T. Y. Wu, PhD: Optimizing Electronic Health Records

Danny TY Wu, PhD, recently joined the biomedical informatics team at the University of Cincinnati as an Assistant Professor with a secondary appointment at Cincinnati Children’s. Wu’s research draws on using human-computer interaction studies, data mining, information retrieval, and natural language processing to maximize the value of clinical data stored in electronic health records. His goals are to improve care quality and support clinical and translational research. In the realm of clinical workflow analysis, he aims to conduct novel and mixed-method workflow analysis to uncover hidden patterns of clinicians’ work processes, identify significant bottlenecks, and inform a better design of health IT solutions. He is conducting research to improve the use of a medical information retrieval tool called Electronic Medical Search Engine (EMERSE), which can serve as a core tool to access free-text data. Other work involves improving the readability and the comprehensibility of clinical notes for patient communication and a new project to improve medication safety through better detection of weight entry errors using artificial intelligence.