A Recommendation System for Patient Diagnosis to Bed Allocation in Hospital Using Deep Learning

This paper describes a full pledged website and mobile app to provide a solution for people who are searching for medical treatment location where they are unaware about its location. With the help of Machine learning algorithms, medical diagnosis will be done and based on the reports of medical diagnosis with the tracking facility of GPS technology, our suggested system will give recommend a nearby hospitals based on user symptoms. This suggested hospital will give the best care for their medical condition; in this paper, we have features with option based on symptom-based prediction, location-based prediction and real-time prediction to book ambulances within the application and also from the selected hospital and a real-time distance will be displayed to the suggested hospital from the user location. This project provides a user-friendly interface which includes the Random forest Machine Learning prediction for using the services which is designed and implemented which gives the precise location tracking for smooth communication and safer travel. Software require some of cover tools for developing mobile app, such as Android and React Native, while hardware requirements of GPS modules, GSM modems, and microcontrollers being used with IoT facility. This project aim to increase patient benefiting features by improving availability to access the healthcare services for people who are in unfavorable conditions being helped using location-based services and also with mobile technologies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.