A Dual transformer-based LLaMA framework for efficient disease prediction and drug recommendation in healthcare

Key Points

• The dual transformer-based framework shows improved accuracy in disease prediction and drug recommendation.
• In preliminary tests, prediction accuracy surpassed 85% on a health dataset spanning over five years.
• Analysis utilizes a novel transformer model designed for machine learning applications in healthcare data.
• These findings highlight the potential for AI algorithms to significantly enhance patient care and treatment options.