Silvia Burti , Tommaso Banzato , Simon Coghlan , Marek Wodzinski , Margherita Bendazzoli , Alessandro Zotti
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Notable studies are discussed, demonstrating AI's potential for improved accuracy in detecting and classifying various abnormalities.</p><p>The ethical considerations of using AI in veterinary diagnostics are also explored, highlighting the need for transparent AI development, accurate training data, awareness of the limitations of AI models, and the importance of maintaining human expertise in the decision-making process. The manuscript underscores the significance of AI as a decision support tool rather than a replacement for human judgement.</p><p>In conclusion, this comprehensive manuscript offers an assessment of the current landscape and future potential of AI in veterinary diagnostic imaging. It provides insights into the benefits and challenges of integrating AI into clinical practice while emphasizing the critical role of ethics and human expertise in ensuring the wellbeing of veterinary patients.</p></div>","PeriodicalId":21083,"journal":{"name":"Research in veterinary science","volume":"175 ","pages":"Article 105317"},"PeriodicalIF":2.2000,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0034528824001838/pdfft?md5=47a045a989df859b813a3b072b74ebd0&pid=1-s2.0-S0034528824001838-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations\",\"authors\":\"Silvia Burti , Tommaso Banzato , Simon Coghlan , Marek Wodzinski , Margherita Bendazzoli , Alessandro Zotti\",\"doi\":\"10.1016/j.rvsc.2024.105317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This manuscript provides an overview of the current state and future prospects of AI in veterinary diagnostic imaging.</p><p>The manuscript delves into various applications of AI across different imaging modalities, such as radiology, ultrasound, computed tomography, and magnetic resonance imaging. Examples of AI applications in each modality are provided, ranging from orthopaedics to internal medicine, cardiology, and more. Notable studies are discussed, demonstrating AI's potential for improved accuracy in detecting and classifying various abnormalities.</p><p>The ethical considerations of using AI in veterinary diagnostics are also explored, highlighting the need for transparent AI development, accurate training data, awareness of the limitations of AI models, and the importance of maintaining human expertise in the decision-making process. The manuscript underscores the significance of AI as a decision support tool rather than a replacement for human judgement.</p><p>In conclusion, this comprehensive manuscript offers an assessment of the current landscape and future potential of AI in veterinary diagnostic imaging. 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Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations
The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This manuscript provides an overview of the current state and future prospects of AI in veterinary diagnostic imaging.
The manuscript delves into various applications of AI across different imaging modalities, such as radiology, ultrasound, computed tomography, and magnetic resonance imaging. Examples of AI applications in each modality are provided, ranging from orthopaedics to internal medicine, cardiology, and more. Notable studies are discussed, demonstrating AI's potential for improved accuracy in detecting and classifying various abnormalities.
The ethical considerations of using AI in veterinary diagnostics are also explored, highlighting the need for transparent AI development, accurate training data, awareness of the limitations of AI models, and the importance of maintaining human expertise in the decision-making process. The manuscript underscores the significance of AI as a decision support tool rather than a replacement for human judgement.
In conclusion, this comprehensive manuscript offers an assessment of the current landscape and future potential of AI in veterinary diagnostic imaging. It provides insights into the benefits and challenges of integrating AI into clinical practice while emphasizing the critical role of ethics and human expertise in ensuring the wellbeing of veterinary patients.
期刊介绍：
Research in Veterinary Science is an International multi-disciplinary journal publishing original articles, reviews and short communications of a high scientific and ethical standard in all aspects of veterinary and biomedical research.
The primary aim of the journal is to inform veterinary and biomedical scientists of significant advances in veterinary and related research through prompt publication and dissemination. Secondly, the journal aims to provide a general multi-disciplinary forum for discussion and debate of news and issues concerning veterinary science. Thirdly, to promote the dissemination of knowledge to a broader range of professions, globally.
High quality papers on all species of animals are considered, particularly those considered to be of high scientific importance and originality, and with interdisciplinary interest. The journal encourages papers providing results that have clear implications for understanding disease pathogenesis and for the development of control measures or treatments, as well as those dealing with a comparative biomedical approach, which represents a substantial improvement to animal and human health.
Studies without a robust scientific hypothesis or that are preliminary, or of weak originality, as well as negative results, are not appropriate for the journal. Furthermore, observational approaches, case studies or field reports lacking an advancement in general knowledge do not fall within the scope of the journal.
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