An AI-Assisted Early Prevention System Prototype for Assisting Clinical Decision Making in Primary Care

Traditional methods of identifying patients from primary care often rely on manual screening and patient self- reporting, which can lead to delays in treatment and missed opportunities for early intervention. The project aims to leverage Artificial Intelligence (AI) and Machine Learning (ML) algorithms to identify patients in a primary care setting who may require early intervention for common health conditions. This proactive approach aims to improve patient outcomes, reduce the burden on healthcare systems, and provide a more personalized healthcare experience.