MedGo: A Chinese Medical Large Language Model

TL;DR

MedGo is a Chinese medical large language model trained with diverse data types, achieving top performance in medical benchmarks and demonstrating practical deployment at a hospital to enhance medical information processing and decision support.

Contribution

This paper introduces MedGo, a novel Chinese medical large language model trained with specialized data, achieving state-of-the-art results and practical deployment in a hospital setting.

Findings

MedGo achieved first place in the CBLUE benchmark.

MedGo outperformed the base model Qwen2 on ClinicalQA.

MedGo was successfully deployed at Shanghai East Hospital.

Abstract

Large models are a hot research topic in the field of artificial intelligence. Leveraging their generative capabilities has the potential to enhance the level and quality of medical services. In response to the limitations of current large language models, which often struggle with accuracy and have narrow capabilities in medical applications, this paper presents a Chinese medical large language model, MedGo. MedGo was trained using a combination of high quality unsupervised medical data, supervised data, and preference alignment data, aimed at enhancing both its versatility and precision in medical tasks. The model was evaluated through the public CBLUE benchmark and a manually constructed dataset ClinicalQA. The results demonstrate that MedGo achieved promising performance across various Chinese medical information processing tasks, achieved the first place in the CBLUE evaluation. Additionally, on our constructed dataset ClinicalQA, MedGo outperformed its base model Qwen2, highlighting its potential to improve both automated medical question answering and clinical decision support. These experimental results demonstrate that MedGo possesses strong information processing capabilities in the medical field. At present, we have successfully deployed MedGo at Shanghai East Hospital.