What Are The Applications of Artificial Intelligence in Veterinary Medicine?

Ad Blocker Detected

Our website is made possible by displaying online advertisements to our visitors. Please consider supporting us by disabling your ad blocker.

The involvement of AI in veterinary medicine opens up new possibilities to safeguard animal health with as much surefootedness as human health.

There are many who rightly feel that the term ‘healthcare’ shouldn’t be associated with only human treatments, medication and therapy alone. Your pets and animals other than humans need as much, if not more, care as they cannot aptly communicate their distress with anyone in times of a health issue. However, in recent times, the veterinary workforce crisis—issues that include a lack of veterinary doctors and facilities—has impacted animal healthcare adversely. Therefore, the need of the hour is the use of intelligent automation tech in the field. After all, several applications of AI are present in healthcare already. That can be used as a blueprint for incorporating various applications of AI in veterinary medicine and treatments too.


Veterinary Cancer Diagnosis

Cancer is endlessly diverse and complex. Besides, beyond a certain stage, death becomes an inevitability in patients. The complexity factor goes to the next level when you consider the massive number of variations in structure and composition not just between different animals but even among different sub-species within any given taxonomic strand.

Advances in big data analytics, machine learning and computer vision allow healthcare experts to diagnose cancer faster in human beings. Similarly, machine learning can be used to determine abnormal cellular growth in different animals. To develop such applications of AI in veterinary medicine for cancer diagnosis, data scientists in oncology can train AI models with visuals of affected and unaffected cells, tissues and organs of different animals to clearly detect malignancy and avoid or slow down eventual metastasis.

Computer vision is critical for understanding the severity of infection in cellular clusters found in animals. Once detected, such clusters can be dealt with by vets via a drug-driven approach or surgery.

Recently, the Ministry of Education and Science in Poland reported that a team of healthcare data experts developed a machine learning-based tool for early cancer detection in animals.

Animal Radiograph Analysis and Interpretation

Up to a certain degree and on specific occasions, even seasoned vets may find the task of accurately interpreting X-rays and radiographs of an animal’s body challenging. The process can be simplified by using AI for the purpose. Computer vision and machine learning can scan the X-rays of animals to find results that are not discernible to the human eye. This application of AI in veterinary medicine helps medical experts in finding problematic bone formations and other hard-to-track issues easily, facilitating quicker treatment for recovery.



Source: AVMA

As with other applications of machine learning in healthcare, AI-based veterinary tools can be invaluable assets for vets to carry out their job with greater effectiveness and efficiency.