This research introduces a novel framework that leverages Large Language Models to automatically construct comprehensive Patient Journey Knowledge Graphs (PJKGs) from unstructured clinical consultations.

• Transforms fragmented healthcare data into interconnected knowledge networks
• Accurately extracts and relates medical entities, treatments, symptoms, and patient interactions
• Achieves 88% accuracy in knowledge graph construction with minimal human intervention
• Enables more coordinated care and personalized interventions across the healthcare spectrum

This innovation addresses critical needs in the medical sector by providing a holistic view of patient trajectories, supporting better clinical decision-making, and improving care coordination through advanced data representation.

From Patient Consultations to Graphs: Leveraging LLMs for Patient Journey Knowledge Graph Construction