Construction and Application of Holistic Artificial Intelligence System for Medical Large Language Models

Large language models (LLMs) are recognized for their powerful self-learning and understanding skills, as well as their huge development potential and application value in medical domain. However, current LLMs in the medical field are marked by an urgent demand for a large amount of pre-training data, high computing power costs, and a lack of standardized standards and indicator systems, which greatly limits its expansion and application. To address the above-mentioned issues, a systematic large-scale modeling framework is proposed for the whole medical process service scenario. Knowledge factorization and dynamic resource management methods are utilized in this framework to achieve model simplification and native network construction, enabling elastic deployment and flexible configuration of the models. The reliance on computational resources is reduced to some extent by this approach. Furthermore, blockchain technology is incorporated into the framework to ensure the security and trustworthiness of medical data. By introducing the concept of holistic artificial intelligence, a holistic artificial intelligence system framework for the medical field is constructed, aiming to promote the rapid implementation and sustain healthy development of medical LLMs. © 2024 Beijing University of Posts and Telecommunications. All rights reserved.