The advent of Artificial Intelligence (AI) in the field of modern medicine can be considered revolutionary as this technology enables intelligent clinical data analysis and early detection of possible diseases. This paper suggests Artificial Intelligence-Driven Healthcare System for Early Risk Detection and Patient Guidance aimed at predicting the health risk level of a patient and recommending corresponding action based on symptoms analysis using machine learning algorithms. The proposed system uses a trained Random Forest model for classifying the patients into two categories, namely, High Risk or Low Risk based on age, blood pressure, and glucose level parameters. Moreover, in addition to the classification algorithm, the system performs analysis of the user-entered symptoms and makes preliminary recommendations regarding actions to be taken in order to improve patients' health condition. User inputs and system outputs are saved as a log file in the CSV format, while the interactive dashboard allows visualizing past health trends. The proposed solution was built using Python, Flask, Pandas, and Scikit-learn packages. The experimental results demonstrate the efficiency and speed of this approach as well as its potential to be used as a decision support tool.

Keywords - Artificial Intelligence, Healthcare System, Machine Learning, Random Forest, Health Risk Prediction, Symptom Analysis, Clinical Decision Support, Flask Web Application.