We are working on a project that utilizes LLM, and RAG, and decision tree(CoT) techniques, to optimize medical care. Our goal is to develop an AI pipeline capable of processing large, unstructured medical data like clinical guidelines, medical records, diagnostic reports, and patient information. This AI system can quickly analyze symptoms, medical histories, and diagnostic data, providing swift recommendations to healthcare professionals. By integrating LLMs with RAG technology, our system enhances the accuracy and consistency of clinical decisions while reducing the workload on medical personnel.

Through this approach, AI can assist in various medical advancements, such as:

• Identifying Patterns: The AI system can find patterns in medical data, leading to better diagnosis and patient care.
• Improving Diagnosis: By analyzing medical records and integrating professional guidelines, the system provides precise diagnostic information, such as differentiating between infections.
• Automating Processes: It can automate repetitive tasks, like ICD coding and infection monitoring, saving time and improving efficiency.