In the modern world, patients often face challenges in obtaining timely and accurate medical diagnosis for their symptoms. Traditional habits and the human tendency to self-diagnose through Google searches leads to inaccurate results and causes unwarranted fear and anxiety. The largest issue prevalent in these methods is the lack of personalization leading to generalized, vague and often completely irrelevant search results. Not only does this generate a state of confusion in the user but also delays treatment. There is hence a need for a reliable and personalized algorithm that accurately identifies and diagnoses individual symptoms yet also streamlines the process of booking doctor appointments based on the urgency and severity of the condition. This project aims to leverage advanced technologies, such as artificial intelligence and machine learning, to analyze patient-specific data and provide tailored recommendations for both symptom understanding and appointment scheduling. Our goal is to reduce the cases of inaccurate self-diagnosis and facilitate timely access to appropriate medical care, ultimately improving health outcomes for individuals.