Amit SahaAmit K Saha is an Assistant Professor, Clinical Data Scientist in the Department of Anesthesiology at Wake Forest School of Medicine, Winston-Salem, NC. He is responsible to drive an optimal data architecture that efficiently and effectively presentsan integrated view of clinical data for operational, financial and research processes. Also serving as a leader for data governance, best practices and optimal use of information to support the goals of the department. Supporting the research interests of faculty in the department. Previously he worked as Worked as the member of Center for Distance Health evaluation and analysis group at University of Arkansas Medical Sciences with the focus on achievement of key quality metrics to provide better patients care and outcome. His research interest includes Healthcare Informatics, Patient Care Data Management, Quality Improvement, natural language processing (NLP) and Social Computing. His long-term goal is to build a patient care experience research model using informatics approaches of data mining and predictive analytics methodology which will be of help for patient care decision support and help researchers answer key research questions. Electronic health records along with clinical data which includes both structured and unstructured text can be analyzed for knowledge and care improvement. By applying natural language processing (NLP), data standardization, mining, and analysis tools to various patient response data model can help in making better decisions in the planned patient care process. He along with his advisor Dr. Agarwal has examined various cyber campaigns such as Autism support groups’ efforts to debunk misinformation campaigns. The research has resulted in the best paper award at Fifth International Conference on Social Media Technologies, Communication, and Informatics (SOTICS 2015), Barcelona, Spain and publication in other journal articles, and conference proceeding papers. Dr. Saha obtained Ph.D. from the University of Arkansas at Little Rock with outstanding dissertation recognition. Read More Read Less
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