Research on Behavioural Recognition Analysis Based on Deep Learning and ADD-MAP System

In this paper, we propose a medical service platform for disease analysis based on action recognition algorithms, ADD-MAP (Advanced Animal Disease Monitoring and Analysis Platform), which aims to enhance animal behavior research through deep learning technology scientific and ethical nature of animal behavior research through deep learning technology. Firstly, the core driving force of the platform is MIDA-Net deep neural network, which integrates a large amount of primate and rodent experimental data through machine autonomous learning algorithms, and has the ability of multi-animal action recognition and disease analysis with high accuracy. Secondly, with the introduction of action recognition algorithms, users only need to upload videos of spontaneous animal behaviors, and ADD-MAP will be able to quickly and accurately recognize the behaviors and provide reference probabilities of disease possibilities based on the analysis of action patterns. Finally, in terms of non-invasive diagnosis, the ADD-MAP platform supports scientific decision-making for drug development and personalized treatment strategies by providing accurate disease models and database comparison functions. In addition, the user-friendliness of the platform makes it easy to be used by non-specialists, lowering the threshold of AI technology application. To summarize, ADDMAP is of great value in promoting human health, advancing medical science and technology, and enhancing the ethical standards of scientific research, and is a key link between scientific research and practical applications.