Hongfang Liu, Ph.D.

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SUMMARY

The primary research focus of Hongfang Liu, Ph.D., is to facilitate the secondary use of clinical data for clinical and translational science research and health care delivery improvement using data science, artificial intelligence and informatics approaches.

Dr. Liu's research has been extensively funded by the National Science Foundation and the National Institute of Health (NIH) since 2003. Her work accelerates the pace of knowledge discovery, implementation and delivery of improved health care. Dr. Liu is a member of several professional societies, including the American Medical Informatics Association (AMIA) and the International Society for Computational Biology (ISCB).

Focus areas

• Open health natural language processing (NLP). Dr. Liu aims to advance the use of NLP technologies for clinical and translational research and health care delivery through advanced machine learning, privacy-preserving computing and community partnership.
• Accelerate discovery to delivery in digital medicine for clinical excellence. One challenge in applying artificial intelligence (AI) in clinical settings is model validity. Without a scientific rigor process, the validity, implementability and generalizability of AI models can be a significant issue. Dr. Liu aims to develop the infrastructure, tools, processes and expertise to accelerate the discovery to delivery for advancing digital medicine.
• The right knowledge service at the point of care. One potential promise of AI is to ensure the right information and knowledge derived from data are delivered at the right time to the right provider so patients can receive the right care. Dr. Liu aims to identify barriers and challenges in implementing AI in health care, develop electronic health record-agnostic and people-centric innovative solutions, and contribute to institutional priorities.
• Acquiring and applying data-driven evidences for shared decision-making for the primary care setting. Dr. Liu aims to obtain data-driven evidence that overcomes several limitations of prior retrospective and prospective studies. This will translate data-driven evidence into clinical decision support tools and decision aids to develop individualized treatment recommendations and support shared decision-making.

Significance to patient care

Dr. Liu's work in informatics has resulted in informatics systems that unlock clinical information stored in clinical narratives. Her work accelerates the pace of knowledge discovery, implementation and delivery for improved health care.

Professional highlights

• Fellow, American College of Medical Informatics, 2015-present
• Member, Informatics Domain Task Force, National Clinical and Translational Science Awards Consortium, 2015-present
• Leader, Natural Language Processing Working Group, American Medical Informatics Association, 2014-present
• Dr. Richard F. Emslander Professor II, 2019