Nabarun Halder
- Research Assistant, CCDS
Research Interests
Machine Learning, Deep Learning, Natural Language Processing, Health Informatics, Human-Computer Interaction
Conference Paper2024
Design and Evaluation of the PustiPothika mHealth App: A Machine Learning-Enabled Solution for Daily Nutritional Monitoring and Recommendations in Bangladesh
Nabarun Halder, Yousra Tabassum, Anika Islam, Nusrat Sultana, J. M. Sadik-Ul Islam Smaron, Ashraful Islam
IEEE 2024 International Advances in Science & Engineering Technology (ASET) Multi-Conferences
IEEE, pp. 01-07
Abstract
Eating healthy is important, but it is not enough; consuming all the necessary nutrients the body requires is equally important. Nutrients are essential for all bodily systems' growth, repair, and proper functioning. In this study, we have surveyed to understand the views and practices among Bangladeshi people, how they make their dietary choices, and the use of the mobile health (mHealth) app. We developed a mobile application for the people of Bangladesh, where providing physiological information allows the users to know their nutritional needs and make their grocery choices accordingly. We developed a recommendation system that can create a list depending on the user's nutritional requirements, with just a little preference for food items. Through our survey, among 72 participants, 75% wanted this kind of solution and among 10 testers, all of them liked using our system.
Keywords
mHealthComputer science
CCDS Authors
Ashraful Islam, PhD
- Center Director, CCDS
- Director, HCI Wing
Assistant Professor
Department of Computer Science and Engineering
Independent University, Bangladesh (IUB)Research Interests
Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact
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