Artificial intelligence (AI) has been a potent force in transforming the approach toward predicting and diagnosing animal diseases
(Appleby and Basran, 2022). As comprehension of AI applications in healthcare expands, there is an increasing acknowledgment of its capacity to improve veterinary practices, providing inventive resolutions to long-standing difficulties in animal healthcare
(Bohr and Memarzadeh, 2020). The convergence of AI and veterinary medicine offers a distinct chance to enhance disease prediction and diagnosis accuracy, as well as redefine the extent of preventive care and treatment approaches
(Ezanno et al., 2021). This study aims to thoroughly investigate the current state of AI in veterinary healthcare, with a particular emphasis on its use in predicting and diagnosing animal diseases.
Veterinary healthcare has depended on a blend of clinical expertise, diagnostic examinations and medical records to detect and treat animal diseases
(Cassidy et al., 2017). Veterinarians must have a sharp eye for clinical observation, accurate evaluation of laboratory tests and empirical knowledge to diagnose and treat diseases
(Hobson-West and Jutel, 2020). Nevertheless, the drawbacks associated with traditional approaches, such as lengthy procedures and subjective assessments, less precise diagnosis and overreliance on symptomatic treatment have prompted the incorporation of AI technology into the field of veterinary medicine
(Ahuja, 2019). In addition, like any other medical field, the veterinary field can sometimes be resistant to adopting new technologies and methodologies. This resistance may stem from a lack of awareness, training, or a preference for familiar practices. Traditional veterinary care often leans towards a reactive approach, addressing health issues as they arise
(Bazzi, 2022). Insufficient emphasis on preventive measures such as vaccination programs, routine screenings and nutritional planning has been observed, which could help avoid diseases altogether
(Bohr and Memarzadeh, 2020). This lack of emphasis is also affecting the physical health of veterinarians, who are at risk of contracting zoonotic diseases due to their proximity to animals. Zoonotic diseases are a leading cause of human illnesses
(Kinnunen et al., 2022; Cho, 2024;
Hai and Duong, 2024;
Semara et al., 2024; Maltare et al., 2023; Bagga et al., 2024; AlZubi, 2023).
The traditional diagnostic and treatment methods can be resource-intensive, posing barriers for communities with limited resources. Additionally, certain traditional medications and treatments, like overused antibiotics in animal agriculture, can lead to environmental consequences, such as antibiotic resistance and pollution
(Kinsella et al., 2009). Hence, there is an urgent need for immediate efforts to address the current state of animal healthcare to ensure its sustainability. Recently, artificial intelligence (AI) has emerged as a promising tool in veterinary science, contributing significantly to advancements across various facets of animal healthcare. This research paper aims to delve into the intricate world of AI applications in animal disease prediction and diagnosis, encompassing a comprehensive review of the current landscape, identification of challenges and limitations and exploration of future directions.
Current state of veterinary healthcare
Veterinary healthcare plays a pivotal role in preserving and sustaining animal life and enhancing the well-being of human populations by improving rural livelihoods and nutrition. Additionally, it contributes to mitigating global health crises by proactively addressing risks such as the emergence of pandemic diseases, antimicrobial resistance, food contamination and environmental health issues at their source.
Veterinarians employ a multifaceted approach to diagnose and treat illnesses in animals. Beginning with a thorough clinical examination to assess physical health and symptoms, they utilize diagnostic imaging, laboratory tests and microscopic analysis of tissue samples for a comprehensive understanding
(Evason et al., 2021). Genetic testing, allergy testing and specialized diagnostics for infectious diseases aid in identifying underlying causes
(Johnson et al., 2021). Treatment plans, which may include medications, surgery, dental procedures and nutritional management, are tailored to the specific condition. However, preventive care, which involves taking proactive measures to maintain the health of animals and detect potential issues early on, is the cornerstone of animal healthcare
(Evason et al., 2021). This approach aims to prevent diseases, identify risk factors and address health concerns before they become more serious. Regular check-ups, vaccinations and parasite control are crucial in preventing diseases and maintaining overall animal health.
The diagnosis of animal diseases primarily depended on clinical signs and confirmation made through a limited range of laboratory tests and microbiological cultures. This was then improved with the inclusion of radiography and ultrasound. However, it still takes several days for confirmation and sometimes requires outsourcing or referral to specialists
(Perera et al., 2022). Any delay in diagnosis can cause significant damage to public health and industries, especially in the case of infectious diseases. Early detection of diseases allows for timely intervention and improves treatment outcomes
(Evason et al., 2021).
However, there are many challenges faced by veterinarians in diagnosing and treating animals such as difficulty in obtaining accurate information due to limited communication with animals, stress induced in animals during procedures, financial constraints for pet owners and limited resources in certain regions (
Bomzon, 2011;
McKenzie, 2014;
Pun, 2020). Ethical dilemmas arise when balancing the best interests of the animal with owner preferences and financial considerations. Zoonotic risks and the need for owner compliance further complicate the veterinary landscape. Staying abreast of rapid technological advances and managing the emotional toll of difficult cases also contribute to the challenges faced by veterinarians. Overcoming these obstacles requires ongoing professional development, effective communication, preventive care emphasis and collaboration within the veterinary community to provide optimal and compassionate care to animals.
Veterinary medicine is now becoming specialized, with veterinarians focusing on specific areas of expertise, such as internal medicine, surgery, oncology and exotic animal medicine. This specialization allows for more in-depth knowledge and expertise in specific areas, leading to improved diagnostic accuracy and treatment efficacy
(Rosol et al., 2009). In addition, the One Health approach which recognizes the interconnectedness of human, animal and environmental health, emphasizes the need for a collaborative approach to address health challenges that affect multiple species. By working together, veterinarians, physicians, veterinary scientists and public health officials can better understand and control the spread of zoonotic diseases and promote the overall health of humans, animals and the environment
(Velazquez-Meza et al., 2022). Utilizing artificial intelligence as a tool for mechanistic epidemiological modeling is illustrated in Fig 1.
The field of veterinary medicine has witnessed significant advancements in recent years, leading to improved diagnostic tools, more effective treatments and a greater understanding of animal diseases
(Buller et al., 2020). Technological innovations, such as artificial intelligence (AI) and machine learning, are being harnessed to analyze medical images, identify patterns and develop personalized treatment plans. Additionally, regenerative medicine holds promise for repairing damaged tissues and organs, offering new therapeutic options for previously incurable conditions
(Haleem et al., 2021). These innovative approaches, coupled with traditional practices, are paving the way for a more comprehensive and effective veterinary healthcare system. However, these emerging approaches also have limitations. Telemedicine may not be suitable for all cases, especially those requiring hands-on examinations or specialized procedures. AI-powered tools may require extensive data training and validation to ensure their accuracy and reliability. Precision medicine relies on comprehensive genetic and environmental information, which may not always be readily available. Regenerative medicine is still in its early stages of development and its long-term safety and efficacy require further research and clinical trials
(Johnson et al., 2021).
AI application in veterinary medicine
Artificial intelligence (AI) is rapidly transforming the field of animal healthcare, introducing groundbreaking tools and techniques that are enhancing diagnostic accuracy, streamlining treatment planning and optimizing animal well-being. AI applications are revolutionizing various aspects of veterinary care, offering a comprehensive and holistic approach to animal health.
AI-powered behavior analysis and modification
AI is providing valuable insights into animal behavior, enabling veterinarians to identify and address behavioral issues such as anxiety, aggression and stress. AI-powered tools can analyze animal behavior patterns, vocalizations and movement patterns to detect subtle signs of behavioral problems. This information can be used to develop personalized behavior modification plans, improve animal welfare and reduce the risk of behavioral problems
(Aguilar-Lazcano et al., 2023).
Remote patient monitoring and early intervention
AI-enabled wearable devices and sensors are transforming animal healthcare by providing real-time data on animal health parameters. These devices can collect data on heart rate, activity levels, sleep patterns and other vital signs, allowing veterinarians to remotely monitor animal health and detect potential problems early. This remote monitoring capability enables timely intervention, preventing the worsening of health conditions and improving overall animal well-being
(Mitro et al., 2023). With advancements in telecommunications technology, telemedicine has become more accessible in veterinary care. Veterinarians can now conduct remote consultations, provide guidance on animal health concerns and even prescribe medications without the need for in-person visits. This technology is particularly beneficial for rural areas with limited access to veterinary services.
Smith et al., (2022) conducted surveys with 17 access to veterinary care organizations, 516 veterinarians and clinic employees and 1009 animal owners. Their research highlighted the COVID-19 pandemic’s effects, exposing both fresh and worsened difficulties in obtaining and providing veterinary care.
Widmar et al., (2020) reported that there are numerous benefits to veterinary telemedicine for both pet owners and their animal friends. These include avoiding children visiting the clinic, bringing large, nervous, or fearful animals, improving the accessibility of veterinary services in remote areas, providing clients with quick access to advice or triage to decide whether an in-person visit is required, saving time and making use of more flexible consultation hours. They also found that dog owners in the United States were willing to pay an extra $38.04 or $13.38, respectively, for a telemedicine consultation with either their primary care veterinarian or another veterinarian in the vicinity. For cat owners, these figures were $38.12 and $12.74, respectively.
(Widmar et al., 2020).
Cloud computing for data storage and analysis
Cloud computing provides scalable and cost-effective solutions for storing and analyzing large volumes of veterinary healthcare data. By leveraging cloud-based platforms, veterinarians can access medical records, imaging studies and research findings from anywhere with an internet connection, facilitating collaborative research and decision-making.
Bioinformatics for Disease Surveillance and Epidemiology: Bioinformatics tools enable the analysis of large-scale genomic and epidemiological data to track disease outbreaks, monitor antimicrobial resistance and identify emerging infectious diseases in animal populations. These tools play a crucial role in public health surveillance and disease control efforts.
Tran et al., (2024) provided an overview of bioinformatics applications in preventive medicine and epidemiology, showcasing their potential and future prospects.