Abstract
Introduction. The article discusses the problem of using laboratory animals in preclinical research and, as a solution to this problem, the use of modern technologies like artificial intelligence. The aim of the work is to study the application of computer vision methods and large language models for preclinical research. Discussion. Nowadays scientists all over the world are actively trying to replace animal models in preclinical research with more modern solutions. Artificial intelligence plays an important role in this process. It allows us to make research faster and also to improve the quality of experiments, and therefore, it can lead to the decrease in the number of tests, that may turn out to be unjustified and, in most cases, fatal to animals. The use of AI in preclinical research makes it possible to conduct more accurate experiments, reduce the likelihood of unsuccessful research and increase the reliability of the results. It also allows us to reduce the number of animals which are used in experiments, which is one of the main aspects of bioethics. It is possible to reduce the suffering of animals and improve their protection from the negative effects of experiments by replacing them with computer models and AI-based virtual systems. Conclusions. The use of artificial intelligence in preclinical studies is one of the best ways to develop more ethical, accurate and effective scientific methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
