Abstract:The potential of integrating Computer-Assisted Diagnosis (CAD) with Large Language Models (LLMs) in clinical applications, particularly in digital family doctor and clinic assistant roles, shows promise. However, existing works have limitations in terms of reliability, effectiveness, and their narrow applicability to specific image domains, which restricts their overall processing capabilities. Moreover, the mismatch in writing style between LLMs and radiologists undermines their practical utility. To address these challenges, we present ChatCAD+, an interactive CAD system that is universal, reliable, and capable of handling medical images from diverse domains. ChatCAD+ utilizes current information obtained from reputable medical websites to offer precise medical advice. Additionally, it incorporates a template retrieval system that emulates real-world diagnostic reporting, thereby improving its seamless integration into existing clinical workflows. The source code is available at https://github.com/zhaozh10/ChatCAD. The online demo will be available soon.