Danielle Mowery, PhD, FAMIA



Danielle Mowery, PhD, FAMIA

Danielle Mowery, PhD, FAMIA

Assistant Professor of Informatics

Dr. Mowery arrived at Penn in September of 2018. As a collaborative investigator, she develops natural language processing (NLP) solutions for processing clinical texts— i.e., clinical notes, chatbots, and transcribed texts— to support clinical and translational research. She leverages NLP, data science, 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. Furthermore, her solutions focus on helping patients and clinicians make better decisions at the point of care whether its in a traditional hospital 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.

As Chief Research Information Officer in Penn Medicine, she directs the clinical research informatics core within 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 regional, national and international clinical research informatics communities.

Content Area Specialties

Natural language processing, semantics, discourse, knowledge representation, electronic health records, standards, phenotyping, biomedical informatics, clinical informatics, patient-centered outcomes research, clinical research services, clinical decision support, chatbots

Methodology Specialties

Data science, machine learning, rule-based systems, feature selection, classification, visualization

About Us

To understand health and disease today, we need new thinking and novel science —the kind  we create when multiple disciplines work together from the ground up. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. 

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