MedAidDialog: A Multilingual Multi-Turn Medical Dialogue Dataset for Accessible Healthcare

Researchers have introduced MedAidDialog, a multilingual medical dialogue dataset covering seven languages, and developed MedAidLM, a conversational AI model for preliminary medical consultations. The system uses parameter-efficient fine-tuning on small language models to enable deployment without high-end computational infrastructure while incorporating patient context for personalized consultations.

• →MedAidDialog extends existing medical dialogue datasets with synthetic multi-turn consultations across seven languages including English, Hindi, Telugu, Tamil, Bengali, Marathi, and Arabic.
• →MedAidLM uses parameter-efficient fine-tuning on quantized small language models to reduce computational requirements for deployment.
• →The system incorporates patient pre-context information like age, gender, and allergies to personalize medical consultations.
• →Experimental results show the model can effectively perform symptom elicitation and generate diagnostic recommendations through multi-turn dialogue.
• →Medical expert evaluation was conducted to assess the plausibility and coherence of AI-generated consultations.