Dr. Danielle Mowery is a collaborative investigator that develops natural language processing (NLP) and generative artificial intelligence (AI) solutions for processing clinical texts – i.e., clinical notes, chatbots, and transcribed texts – to support clinical and translational research. She leverages NLP, data science, machine learning, and computational methods to integrate and analyze information from unstructured texts and structured clinical data to help clinical investigators better understand disease burden, treatment efficacy, and clinical outcomes. Her solutions focus on helping patients and clinicians make better decisions at the point of care whether it’s in a traditional health system setting or through digital health services within a patient’s home. Her work aims to uncover scientific discoveries, identify actionable healthcare knowledge, and optimize translation of research into patient care. Today, she will review lessons learned by her research team while applying generative AI to support patient phenotyping studies using electronic health records.
As the inaugural Chief Research Information Officer for Penn Medicine, she directs the Clinical Research Informatics Core at the Institute for Biomedical Informatics – a key position designed to bridge the gaps between clinical data, research expertise, and actionable healthcare knowledge. Dr. Mowery represents Penn Medicine in local, regional, national, and international clinical research informatics communities, i.e., formerly, serving as co-chair of the Association of American Medical Colleges (AAMC) Group on Information Resources (GIR) and currently, member of the AAMC Steering Committee, co-chair of the Penn Medicine Data & AI Governance Committee and member of the Epic Cosmos Governing Council. She is also a Fellow of the American Medical Informatics Association. Dr. Mowery has extensive training in the sciences that supports her interests in clinical and translational research including a BS in Biological Sciences, MS in Health & Rehabilitation Sciences, MS and PhD in Biomedical Informatics from the University of Pittsburgh. She completed her post-doctoral training at the University of Utah.