An Integrated Web Based and Application Programming Interfaces for Disease Prediction Through Self Diagnosis

The integration of web-based technologies and APIs (Application Programming Interfaces) has transformed various domains, including healthcare. In this research paper, we present a web-based blood bank system coupled with an API for disease prediction. The objective of this system is to streamline the process of blood donation and provide an efficient platform for disease prediction using advanced algorithms. The web-based blood bank serves as a centralized platform for donors and recipients to interact seamlessly. It facilitates the registration and authentication of blood donors, allowing them to provide essential information such as blood type, availability, and location. Recipients, on the other hand, can search for compatible donors based on their requirements and initiate communication for blood transfusion. Moreover, our system incorporates an API for disease prediction, leveraging machine learning techniques to analyze a wide range of medical diseases symptoms. By utilizing a robust algorithm, the API can predict the likelihood of various diseases based on input parameters such as demographic information, medical history, and lifestyle factors. The predictions provided by the API can aid in early detection and prevention of diseases, enabling healthcare professionals to offer timely interventions and personalized treatments. The implementation of this web-based blood bank and disease prediction API offers several advantages. It enhances the efficiency of blood donation processes, ensuring a timely and accurate match between donors and recipients. Additionally, the disease prediction API empowers healthcare providers with valuable insights, facilitating proactive healthcare management.