Past Events

Past Events

April 3, 2024

• Large-Scale Automated Encoding of Veterinary Diagnoses with Transformer-Based Language Models

• Title: Large-Scale Automated Encoding of Veterinary Diagnoses with Transformer-Based Language Models
  
  Summary: The encoding of medical records into standardized medical terminologies greatly increases the research value of such data by promoting usability, extractability, and interoperability. While some data can be encoded in a straightforward manner using rules-based methods, diagnoses are often recorded as free-text by clinicians and require sophisticated natural language processing (artificial intelligence) methods to encode. Our research builds on previously developed automated encoding methods and publicly available pretrained large language models to achieve state-of-the-art results on a clinically comprehensive scale.

  Mayla Boguslav Bio: Mayla R. Boguslav, PhD is a Postdoctoral Fellow in Mathematics at Colorado State University (CSU) with a research focus on natural language processing. At CSU, her focus is on identifying diagnosis codes from SNOMED-CT for veterinary records with the Data Science Research Institute. In general, she seeks to determine what isn't (yet). She works to uncover our collective scientific questions that are not yet answered by creating taxonomies and using ontologies (controlled vocabularies). Focusing on what science has yet to answer helps researchers locate the role of their ongoing work, clarifies what scientists are saying and what they are not, and rebuilds trust in science. Mayla received the 2023 AMIA Edward H. Shortliffe Doctoral Dissertation Award for her PhD in Computational Biosciences from the University of Colorado Anschutz Medical Campus.

  Adam Kiehl Bio: Adam Kiehl is a Health Data Scientist for Colorado State University’s (CSU) College of Veterinary Medicine and Biomedical Sciences (CVMBS) Research IT team. He recently received a Bachelor’s degree in Data Science and a Master’s of Applied Statistics degree from CSU. As a student intern, he was engaged in a long-term data harmonization project aimed at standardizing CSU’s veterinary electronic health records (EHR) to the OHDSI OMOP common data model. He is now engaged with that project on a full-time basis and his efforts have expanded to include the development of natural language processing (NLP) models to automatically encode free-text veterinary records into the SNOMED-CT medical terminology. His primary professional ambition is to advance CSU’s interactions with health informatics in collaborative and innovative ways.

  David Kott Bio: David Kott is currently a graduate student in Mathematics at Colorado State University (CSU). His research interests lie at the intersection of machine learning and distributed computing. David is dedicated to exploring innovative ways to leverage these fields to solve complex mathematical problems. His work is characterized by a strong commitment to research and a passion for pushing the boundaries of knowledge.

February 7, 2024: Happy New Year Meet & Greet

Noon-1PM

Happy New Year! Our group has grown tremendously over the past year, so we wanted to take time to allow members to introduce themselves and share their background/research. This is meant as a way for us to foster multidisciplinary collaborations, so please jump in no matter your background or stage of training!

Our thought is to allow each person 3-5 minutes to introduce themselves. This should be casual; you don't need a PowerPoint, but 1-2 slides are welcome if you would like.  Please RSVP to kreagan@ucdavis.edu by Jan 31st if you want to participate.

December 6, 2023 - Journal Club: Judit Wulcan

Noon-1PM

Presenter: Judit Wulcan; Topic: Metric-related pitfalls in image analysis validation. Article link here. PDF link here.

October 4, 2023: Parminder S. Basran

Noon-1PM

Parminder S. Basran, PhD FCCPM; Associate Research Professor, Department of Clinical Sciences, Cornell College of Veterinary Medicine. Title: Leveraging computer vision in production animal diagnostics: Moo-ving forward with veterinary AI

Abstract: Veterinary medicine is a broad and growing discipline that includes topics such as companion animal health, population medicine and zoonotic diseases, and health and welfare of food-production animals. In this presentation, we describe some current and novel applications of artificial intelligence in veterinary medicine. Our lab has been investigating machine learning approaches in the dairy industry. We will describe how AI techniques currently adopted in medical image analysis can be used in this setting. These and other AI technologies have the potential to enable more efficient workflows for the veterinarian and provide new insights when managing or treating of disorders. It is our hope that these technologies will translate to better quality of life for animals and those who care for them.

Bio: Parminder S. Basran PhD (2002- University of Calgary), MSc (1997-University of Alberta) is a Associate Research Professor at Cornell University, College of Veterinary Medicine. He is a Member (2004) and Fellow (2010) of the Canadian College of Physicists in Medicine. The Basran Lab, named the Veterinary Artificial Intelligence in Diagnostic Imaging and Radiotherapy (VAIDER Lab), has 3 main areas of focus in Veterinary Medicine: Radiation Dosimetry and Treatment Planning; Medical Image Processing and Analysis​; and Medical Physics Training and Education. Medical imaging processing projects focus on the use of machine learning in veterinary medicine, including multi-omics (Ultrasound + CBC and blood serum) approaches for discriminating lymphoma from inflammatory bowel disease in cats, leveraging machine-learning from x-ray images of the horse fetlock to predict the risk of injury in Thoroughbred racehorses, and adopting computer vision technologies to detect and control mastitis in dairy cows. Radiation dosimetry and treatment planning projects focus on high-precision radiation medicine to animals including limb preservation for dogs diagnosed with appendicular osteosarcoma, the development of standardized radiation dosimetry techniques for accreditation and benchmark performance in veterinary radiation oncology and surveying the technical and human resources in the delivery of safe and effective radiation therapy in the veterinary setting. Projects related to education include the use of gaming technologies such as Lego© and 3D printing in medical physics education and developing open-access educational content for medical physics education in low-to-middle-income countries.

August 2, 2023: Dr. Kornelia Omyla

Noon-1PM
Dr. Kornelia Omyla, Theriogenology Resident, University of California-Davis; Title: Equinity Vision: Artificial Intelligence in horse health monitoring.

June 7, 2023 - Journal Club: Kevin Jacques

Noon-1PM

Presenter: Kevin Jacques, Topic: Convolutional neural networks for image recognition in biomedical sciences.

Article link here. PDF here: JC-2023-06-07_U-Net.pdf

May 8, 2023: Dr. Dan Rudmann

Noon-1PM

Dr. Dan Rudmann, Senior Director of Digital Pathology at Charles River Laboratories. Driving innovation in toxicologic pathology with the digital microscope and machine learning.

Dr. Dan Rudmann is an ACVP board certified veterinary toxicologic pathologist with almost 25 years of experience in the pharmaceutical and biotechnology industries.  He is presently Senior Director of Digital Pathology at Charles River Laboratories.  In this role, Dr. Rudmann is leading the digital transformation for pathology at Charles River. His scientific interests include the application of Deep Learning artificial intelligence models to toxicologic and diagnostic pathology and he leads a global working group investigating AI applications at CRL.  Dr. Rudmann publishes and speaks frequently on Digital Pathology topics and is working with the CRL team to collaborate broadly across the industry in support of pathology digitalization.

April 26, 2023: Inaugural AI in VetMed Happy Hour!

5-7PM

For all local folks, we would like to have an informal get together at Super Owl brewery in West Davis. This will be a time to get to know each other in person and talk about AI in veterinary medicine! 

February 8, 2023: “Everything a veterinarian needs to know about AI in 2023”

Noon-1PM

Presented by Dr. Ryan Appleby, DVM, DACVR, Assistant Professor of Radiology, Ontario Veterinary College, University of Guelph

December 7, 2022: Seminar – Launching an AI Startup

Noon-1PM 

Presenter: Ali Pankowski
Ali is a fourth year veterinary student at the University of California, Davis. She received her Bachelors of Arts in Public Policy and International Affairs at Princeton University. Alongside her sister and CEO Scott Brown, Ali co-founded Transfur, a clinical tool that utilizes AI to process referral records and allow users to search, sort, and filter the data within them. She is interested in pursuing an internship and specialty residency following graduation.  

October 5, 2022 - Journal Club: Stefan Keller  – Infectious disease prediction

Noon-1PM
Article links here and here

August 3, 2022: Seminar – Dr. Matt Lungren

Noon-1PM

Presenter: Dr. Matt Lungren – Amazon Web Services
Clinical Machine Learning – how the concept of ‘One Medicine’ can advance AI in Healthcare

Matt Lungren is Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare. He also holds affiliate positions with UCSF, Duke, and Stanford University.  Prior to joining AWS, Dr Lungren was an interventional radiologist and research faculty at Stanford University Medical School where he led the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). He served as advisor for dozens of early stage startups and large fortune-500 companies on healthcare AI go-to-market strategy. His work has led to more than 100 scientific publications, including work on multi-modal data fusion models for healthcare applications, new computer vision and natural language processing approaches for healthcare specific domains, opportunistic screening with machine learning for public health applications, open medical data as public good, and prospective clinical trials for clinical AI translation. He is also a top rated instructor on Coursera where his course Fundamentals of Machine Learning in Healthcare, designed especially for learners with clinical non-technical backgrounds, has been completed by more than 10k students around the world.

June 8, 2022 - Journal Club: Dr. Stijn Niessen

(originally scheduled for June 1) Noon-1PM

Article links here and here

June 14, 2022: Seminar - Dr. Titus Brown, UC Davis

Campus Facilities for Data and Compute-Intensive Research in SVM - DataLab and the HPC

Time: 12pm-1pm (bring your lunch!)

Location: 1105 VetMed 3B*

This is a faculty forum for learning about some options for using big computers through the campus supported DataLab and HPC. This will be of interest for faculty who are working on large-scale data analysis and simulations and modeling. 20 minutes presentation, 40 minutes Q&A. Please contact ctbrown@ucdavis.edu for recordings if you are unable to attend.

April 6, 2022: Seminar– Presented by Antech Imaging Services

Noon-1PM

AI in Veterinary Radiology by Dr. Mark Parkinson, Director of Next Generation Technology Group in MARS; Dr. Michael Fitzke, AIS AI project within the Next Generation Technology Group; Dr. Diane Wilson, Director of AI and Academic Affairs
Video (Secure access only)

February 9, 2022  – Journal Club: Krystle Reagan

Improving veterinary student awareness of AI in clinical decision making
Article links here and here

December 1, 2021: Rachael Callcut, M.D., M.S.P.H, F.A.C.S. (UC Davis Health)
 

AI in Medicine: Risk & Reward
No recording available

October 6, 2021 – Journal Club

Presented by Picasso Vasquez

August 4, 2021: Beatriz Martinez-Lopez, DVM, MPVM, Ph.D. Professor VME, UC Davis.

Big Data and smart-epidemiology in practice: the value for prevention and control of infectious diseases