University of California, Davis
The primary mentor is Krystle Reagan, DVM, PhD, DACVIM ([email protected]) an assistant professor of small animal internal medicine at the University of California, Davis Veterinary Medical Teaching Hospital. Her research program focuses on the development of novel diagnostic tools and therapeutics for companion animal and zoonotic infectious diseases. She is a board-certified small animal internist with a clinical focus in infectious diseases. Dr. Reagan is a founding member of the Artificial Intelligence in Veterinary Medicine interest group and has robust collaborations with members of the Center for Data Science and Artificial Intelligence Research and the UC Davis DataLab. She has mentored post-doctoral scientists, veterinary house officers, veterinary students, graduate students, undergraduates, and high school students. She also serves as the chief of service for the immunology and virology clinical laboratory.
- Stefan Keller, DVM, PhD, Diplomate European College of Veterinary Pathologists. Dr. Keller is a veterinary pathologist with a research interest in improving diagnostic methods and making clinical decision-making more data-driven. He is the architect behind anna, an interactive software that enhances patient data visualization and integrates machine learning models to aid in clinical decision-making.
- C. Titus Brown, PhD. Dr. Brown is an NIH funded researcher focusing on data intensive biology, bioinformatics, and metagenomics. His laboratory has designed software leading to faster and more efficient utilization of sequencing data. He is the co-coordinator for the NIH Data Commons Pilot Phase Consortium (2018) and Engagement Lead for the NIH Common Fund Data Ecosystem project (2019-present). Further Dr. Brown is the Director for Community Engagement with the UC Davis DataLab.
Description of potential research projects
The Artificial Intelligence in Veterinary Medicine fellowship program at the University of California, Davis School of Veterinary Medicine is the first program of its kind to offer advanced training in the use of AI and machine learning to enhance clinical decision-making to board-eligible or board-certified veterinary specialists. During this fellowship, the candidate will work with an interdisciplinary team including clinical veterinarians and data scientists to conduct clinical trials to develop, improve, and validate AI/ML powered clinical decision-making tools. Research opportunities include the utilization of a robust patient data set to predict the presence of and outcomes of infectious diseases, including antimicrobial resistant bacterial infections and pathogens of zoonotic concern.
Data intensive research, including machine learning and artificial intelligence algorithm development, is increasingly recognized as the future of precision medicine. High-quality, big data, including high resolution raw images of patients, biomarker data, radiologic data, histopathologic data, and genomic data can be utilized to enhance clinical decision-making. Advancements utilizing readily available animal patient data can be applied to the human medical field in areas where veterinary patients may act as a naturally occurring model of human disease. Our laboratory has a proven track record of developing AI/ML driven tools for predicting infections such as leptospirosis in dogs. An assessment of the translation of these tools to human medicine is needed.
Veterinary specialists appropriate as fellows for your research opportunity
Small animal internal medicine, clinical pathology, anatomic pathology, emergency and critical care, radiology, oncology, neurology, or cardiology.
Additional training opportunities
Dr. Reagan’s Laboratory. The candidate will be invited to participate in weekly laboratory meetings and bi-weekly meetings of the laboratory's data science/AI team.
This growing multidisciplinary team consists of computer scientists/programmers, data scientists, and veterinary subject matter experts. Dr. Reagan’s laboratory has access to high-speed computing resources, and training is available.
AI in Veterinary Medicine Interest Group. This group meets every other month and hosts seminars, journal clubs, and research updates that the candidate can take part in. A full calendar of events can be found at https://ai.vetmed.ucdavis.edu/
Data Intensive Biology Laboratory. The laboratory of Dr. C. Titus Brown focuses on biological data analysis and data integration. The laboratory provides regular training in data-intensive biology.
University of California Davis DataLab. The UCDavis DataLab is a cross-university resource that has a mission to promote, foster, and facilitate data science to accelerate discovery and improve student and research success. They provide instructional support to enhance data science skills, including programming, natural language processing, and image recognition. Other services include consultation on research proposals, the structuring of data sets, and input on data analysis and modeling.
UC Davis School of Veterinary Medicine. The SVM includes students within the professional DVM program, graduate programs, and house officers within the Veterinary Medical Teaching Hospital. The VMTH hospital serves over 50,000 patients per year and has the largest house officer training program in the nation. The school also houses a health informatics committee with regular meetings related to the implementation of the common data model and ATLAS tools.
To express interest in the position and for more information, please contact Krystle Reagan at [email protected].