Real-time Prediction of Fluid Resuscitation Rate for Burn Patients: A Web Based Fuzzy Logic Approach

Effective management of burn patients in the early stages of treatment is crucial for ensuring survival and optimal recovery. A key element of this process is proper fluid resuscitation, which is essential for maintaining organ function and preventing potentially fatal complications such as shock. Accurate and timely assessment of fluid needs, depending on the Total Body Surface Area (TBSA) affected and the patient’s Hourly Urine Output (HUO), is therefore critical. To address these challenges in burn care, this research introduces a modern web application specifically designed for healthcare providers. The application modern technologies, including Spring Boot, React, Node.js, MySQL Database and a Java fuzzy logic library, to implement fuzzy logic design and modeling based on the Rule of Nines. This application facilitates rapid analysis of burn extent and provides continuous 24-hour monitoring. By offering accurate, hourly recommendations for fluid resuscitation rates, the tool significantly enhances decision-making in critical care settings. The application includes secure doctor login functionality, allowing healthcare professionals to manage patient data efficiently. Patient information is stored in a database for real-time access and ongoing monitoring. The user-friendly interface allows for seamless data entry and quick interpretation of results, making it highly practical in high-pressure emergency situations.