The rapid advancement of technology has significantly improved the healthcare sector through intelligent systems that assist in medical diagnosis and patient care. This research paper presents the development of an AI-based Medical Symptom Checker Web Application designed to provide preliminary health guidance to users based on their symptoms. The system allows users to input symptoms through text, speech, or images, which are processed using techniques from Artificial Intelligence, Machine Learning, and Natural Language Processing. The application analyzes the symptoms and predicts possible diseases using trained machine learning models. It then provides basic medical suggestions and recommendations for further consultation if necessary. The system aims to improve accessibility to healthcare information and assist users in early symptom assessment .The results demonstrate that AI-based healthcare tools can enhance digital health services and support medical awareness while complementing professional medical consultation The arrival of modern technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Deep Learning (DL) has brought big changes in healthcare, offering new ways to provide personalized care by improving the quality of various medical services. Our approach involves creating a medical chatbot based on BERT, which uses advanced deep learning technology to improve communication and make healthcare more accessible. Traditional medical chatbots often have problems like not understanding medical conversations well, giving incorrect responses to medical terms, and not being able to offer personalized help. We use BERT, a powerful deep learning model, to solve these issues. The performance of our chatbot is very good. It has an accuracy of 98%, which means it handles medical questions with high precision. A precision score of 97% shows that the responses are accurate and reliable. The proposed web application is designed to provide quick and accessible healthcare guidance, especially for individuals who may not have immediate access to medical professionals. By analyzing the symptoms entered by users, the system generates possible disease predictions and provides basic medical recommendations. This helps users understand the severity of their symptoms and decide whether professional medical consultation is necessary. In addition, the system integrates chatbot functionality to enable interactive communication with users. The chatbot can answer common health-related questions and provide guidance in a conversational manner. Advanced language models such as BERT (Bidirectional Encoder Representations from Transformers) can be used to improve the accuracy of symptom interpretation and response generation. The main objective of this research is to design and implement an intelligent web-based system that improves accessibility to preliminary health information while reducing the workload on healthcare institutions. Although such systems cannot replace professional medical diagnosis, they can serve as a helpful first step in guiding patients toward appropriate healthcare services. The study demonstrates how AI-powered healthcare tools can enhance digital healthcare services and contribute to more efficient and accessible medical support.
Artificial Intelligence, Symptom Checker, Machine Learning, Healthcare Technology, Web Application.
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