AI and Data Science in Veterinary Medicine: Real-World Impact

Data science is an interdisciplinary field that combines the following keystone disciplines: math, statistics, computer science, and domain knowledge. The goal of data science is to extract meaningful and actionable insights from data.

The rise of databases and information systems, along with the rapid evolution of computation and cloud computing have changed the landscape, and with the addition of Artificial Intelligence, will continue to do so at rates that we cannot imagine. Both in Veterinary Medicine and Animal Science, data science is not an aspirational topic anymore, but a reality in application, though the educational efforts are in need to be improved.

Here are some examples of areas in which data science is changing decision making and action at all levels including government inspection and regulation, academic research, farming, and vet clinics.

1. Animal Health and Disease Management

• Data science and cloud computing enables the integration of large clinical, genetics, microbiome, and epidemiological datasets

• Helps veterinarians detect patterns, scale disease surveillance, forecast outbreaks, and design novel preventive strategies

Examples:

a) Swine Medicine - the use of pen-based oral fluids (Dr. Jeff Zimmerman and collaborators, Iowa State University) has helped scaling local, regional, and country-wise surveillance of pig pathogens and/or exposure through serology, which allows for more sampling since animals are not being individually sampled, thereby improving animal well-being, and permitting more sampling and population-based diagnostics. With pen-based oral fluids, temporal sampling becomes affordable, and by using a combination of serology and multiplex qPCR a variety of pathogens (and pathogen exposure) can be monitored. In return, that generates a lot of data across growing-finishing barns across regions that need to be modelled using statistics and other approaches like machine learning. Had this approach not being available, we would be left with sampling animals at the abattoir, which is still helpful for specific purposes such as lung imaging for prediction and modeling of pneumonia at the population level, for instance. Pen-based oral fluids also allow for screening for exotic pathogens which impacts biosecurity at a country level.

2. Livestock Production and Efficiency

• Farms generate large amounts of data generated from sensors, robotics, feed records, milk meters, and genetic evaluations

• Data science allows for optimization of feed efficiency, reproduction performance, and growth/productive strategies

Examples:

a) Dairy farming - dairy production operations, especially the robotized systems but not limited to, are a “gold mine” of data. Dairy cows produce a daily register of feed consumption, milk yield, fat/protein %, mastitis, among other variables, that can now be modelled using data science techniques to identify: 1) the correlation pattern across variables; 2) the impact of explanatory variables on production; 3) bin animals according with parity and productivity to uncover their metrics and how to improve feed efficiency and milk yield; 4) develop predictive forecasting models and validate predictions with data; 5) measure the residual impact of one lactation on another; and 5)use microbiome and microbial whole-genome sequencing to better understand the cause of mastitis and ketosis, improve feed efficiency and strategies related to mitigating methane emission, etc.

3. Food Safety and Public Health

• Data science helps track pathogens across the food chain, assess risk, and refine epidemiological/ecological inquiries

• Veterinary science overlaps with human health in seeking to understand and mitigate zoonotic diseases (e.g., avian flu, coronaviruses, salmonella, etc.)

Examples:

a) Whole-genome sequencing: Bacterial whole-genome sequencing has allowed for a much higher degree of resolution be applied to epidemiological investigations in attempt to tracking pathogens. The most successful example of that in the USA is the FSIS driven surveillance of poultry operations (post-harvest) for Salmonella enterica, and the free availability of genomic data on NCBI Pathogen Detection repository allowing for a large-scale data driven analysis of many thousands of genomes (> 700,000 Salmonella enterica genomes) to identify emerging genotypes, AMR profiles, and attempt to predict transmission. Yet, there remain many challenges with that including improving the quality of epidemiological metadata, do real-time large scale predictive modeling to identify novel mutations and loci associated with emerging patterns, etc.

SARS-COV2 surveillance became another clear example of the positive impact of data science allowing for changing real-time decision making for pathogen control, and the development of more effective vaccines or vaccination strategy with a broaderstrain coverage. Avian influenza surveillance demands moving in that direction for large scale monitoring across wildlife reservoirs and livestock operations.

Other areas where data science has the potential to be beneficially impactful are:

4. Global Agricultural Challenges

• Feeding a growing population requires sustainable, efficient animal production

• Data science can help reduce waste, improve productivity and economics, along with balancing environmental impacts perhaps by leading to better strategic decision-making on where to produce what and how

5. Veterinary clinics

• Data science can improve and fasten disease diagnostics with the use of gut microbiome, X-ray, and sensor-based data in pets and horses

6. Wildlife and Environmental Conservation

• Animal science extends to ecosystems including biodiversity monitoring, endangered species protection, and habit management

• Data science can help processing remote sensing, GPS collars, and camera trap data more efficiently

Reference:

OpenAI, 2025. ChatGPT version 5, accessed on September 26 th , 2025, generated responses that contributed to the content of this blog.

Iowa State University College of Veterinary Medicine News. Accessed on September 26 th , 2025. http://vetmed.iastate.edu/article/oral-fluid-testing-has-transformed-veterinary-diagnostic-medicine/