International Conference on Advancements in Computing [ICAC]

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/312

The International Conference on Advancements in Computing (ICAC) is organized by the Faculty of Computing of the Sri Lanka Institute of Information Technology (SLIIT) as an open forum for academics along with industry professionals to present the latest findings and research output and practical deployments in computing.

The primary objective of ICAC is to promote innovative research that addresses real-world challenges and contributes to the social well-being of communities. The conference provides a dynamic platform for researchers from around the world to present groundbreaking findings, exchange ideas, and establish meaningful collaborations.

https://icac.lk

Browse

Filters

20211

Advanced Search

Filter by

Settings

Author: search.filters.author.Gunarathne, G.W.D.A.

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    PublicationEmbargo
    Mobile Medical Assistant and Analytical System for Dengue Patients
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Jayampathi, K.T.K.; Jananjaya, M.A.C.; Fernando, E.P.C.; Liyanage, Y.A.; Pemadasa, M.G.N.M.; Gunarathne, G.W.D.A.
    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.