Yonghui Wu, Ph.D.
Yonghui Wu, Ph.D.
Department of Health Outcomes & Biomedical Informatics,
UF College of Medicine
Dr. Wu’s research interests are artificial intelligence (AI) techniques, e.g., natural language processing (NLP) and machine learning.
What are your current research interests and/or what is a project you are currently working on?
My research interests are artificial intelligence (AI) techniques, e.g., natural language processing (NLP) and machine learning. I’m currently leading a PCORI-funded project (ME-2018C3-14754) to train computers to understand patient’s social determinants of health (SDoH) information documented in clinical narrative and assess how these SDoH could affect the risk of cancer. People interact with the environment at different levels in a large social system. Individuals’ health outcomes are determined through a complex interplay of multi-level factors including both social determinants of health (e.g., education, employment, social cohesion) and behavioral determinants of health (e.g., smoking). Nonetheless, these important variables are scarcely documented in structured medical codes but are often available in narrative clinical text. This project will fill the gap of using SDoH information for clinical research.
How did you end up going into medicine and/or why did you decide on your specialty?
I believe that artificial intelligence (AI) can help fill many gaps in medical research. Also, doing research with real patient data is much more challenging and the research outcomes have a potential impact on the health care of patients. Electronic health record (EHR) data is a crucial resource for research, yet there are many challenges as EHR data include both structured, coded data and unstructured data such as narrative notes. My expertise in AI, especially natural language processing and machine learning, can help discover the full potential of EHR data.
Why did you decide to focus on cancer?
As one of the leading causes of death, there has been a great amount of effort and resources invested in the treatment of cancer. Yet, many details about this disease are still unknown. Now, we have large volumes of patient data available electronically, which is a great resource to help improve our understanding and treatment of cancer. It’s a great opportunity to apply my expertise in AI to assess more cancer risks and detect potential treatment signals (e.g., drug repurposing) to improve our understanding of cancer and speed up new cancer treatment development.
What excites you about your work? What is exciting to you about your field right now?
AI is developing rapidly in the recent decade. More and more milestones and breakthrough technologies are changing every aspect of life. I’m very lucky to stand at the intersection of AI and medicine at a right time. With the rapid development of AI technologies, I see a great opportunity to use AI to improve medicine and health care.
What do you like to do outside of work?
I like boating and fishing with my wife and two sons. Sea fishing is the best sport to help relax – I have to focus on the new rules defined by the sea and totally forget everything that happened on the land. The crappie and bass in nearby lakes, fresh shrimp in the St. Johns River, scallops and oysters hiding under the sea are a beautiful memory of my family.