Overview
Shelley Rusincovitch, MMCi, is an informaticist and technical leader who specializes in healthcare applications of artificial intelligence and machine learning, data modeling, and data science experiential learning. She has more than 20 years of experience in clinical research including clinical trials, registries, and health system data warehousing.
Ms. Rusincovitch serves as the managing director of Duke AI Health, a multidisciplinary, campus-spanning initiative housed within the Duke …
Ms. Rusincovitch serves as the managing director of Duke AI Health, a multidisciplinary, campus-spanning initiative housed within the Duke …
Current Appointments & Affiliations
Senior Dir, IT
Biostatistics & Bioinformatics,
Basic Science Departments
In the News
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Recent Publications
Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.
Journal Article J Am Med Inform Assoc · April 1, 2017 OBJECTIVE: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. MATERIALS ... Full text Link to item CiteUsing electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.
Journal Article Contemp Clin Trials · January 2016 BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms th ... Full text Open Access Link to item CiteSubstance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data.
Journal Article Drug Alcohol Depend · November 1, 2015 BACKGROUND: Comorbid diabetes and substance use diagnoses (SUD) represent a hazardous combination, both in terms of healthcare cost and morbidity. To date, there is limited information about the association of SUD and related mental disorders with type 2 d ... Full text Open Access Link to item CiteRecent Grants
Enhanced X-ray Angiography Analysis and Interpretation Using Deep Learning
ResearchProject Lead · Awarded by Vigilant Medical · 2019 - 2022Machine learning driven transthoracic echocardiographic analysis and screening for cardiac amyloidosis
ResearchProject Lead · Awarded by Vigilant Medical · 2020 - 2021Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE)
Clinical TrialInformatics Project Leader · Awarded by Patient-Centered Outcomes Research Institute · 2015 - 2020View All Grants