Mobile Medical Assistant and Analytical System for Dengue Patients

Abstract

Dengue fever is a vector-borne viral disease spread by the mosquito Aedes Aegypti. It is a public health problem, with an estimated 50-500 million infections each year and no effective vaccination. People's hectic schedules may not have enough time to see a doctor every time they have a fever. They may overlook their disease, believing it to be a common ailment. Prior medical assistance for dengue patients with fever to check their conditions reliably is a major problem. There is no easily accessible proper system to identify dengue patients at an early stage. This paper presents a mobile medical assistant and analytical system for dengue patients. With a novel approach, using the most appropriate technologies, the mobile application supports identifying dengue patients using the chatbot, analyzing skin conditions, analyzing blood reports, and analyzing dengue-infected areas' functionalities. The registered users can log in to the system and check their dengue condition. The development is carried out with Natural Language Processing, Artificial Neural Network (ANN), Machine Learning, Image Processing, Convolutional Neural Network (CNN), and Android technologies. A mobile application prototype is created and tested, with the possibility of future testing and implementation. The results show effective performances in analyzing dengue conditions.