Namaa: AI-Based System for Screening Child Malnutrition
Supervisor Name
Shadi Abudalfa
Supervisor Email
shadi_abudalfa@hotmail.com
University
Onaizah Colleges
Research field
Artificial Intelligence
Bio
Shadi Abudalfa received the BSc and MSc degrees in Computer Engineering from the Islamic University of Gaza (IUG), Palestine, in 2003 and 2010, respectively. In 2013, he joined King Fahd University of Petroleum and Minerals (KFUPM) as a full-time scholarship student to pursue his PhD degree. He received his PhD in Computer Science and Engineering (CSE) from KFUPM in 2018. Abudalfa has extensive teaching experience, including his previous position as an Assistant Professor at the University College of Applied Sciences, Palestine. He subsequently worked as a Research Scientist at the SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), KFUPM, Saudi Arabia. He is currently an Assistant Professor at Onaizah Colleges, Saudi Arabia. From July 2003 to August 2004, he worked as a Research Assistant at the Projects and Research Lab at IUG, while also serving as a Teaching Assistant in the Faculty of Engineering at IUG. He has served as a reviewer for various international conferences and journals and has co-organized shared tasks, sessions, and workshops at international conferences. His current research interests include artificial intelligence, data mining, human activity recognition, Arabic natural language processing, and sentiment analysis.
Description
Namaa is an AI-based system designed to support the screening of child malnutrition through the analysis of child images and basic demographic information. The project leverages private datasets accessed through formal permission and ethical approval that were previously annotated for malnutrition assessment and validated using growth standards and anthropometric equations established by the World Health Organization (WHO). By building upon medically recognized reference frameworks, the system aims to ensure methodological reliability while exploring how artificial intelligence can assist in identifying children at potential nutritional risk. Namaa is intended strictly as a supportive screening tool and does not replace clinical diagnosis or professional medical assessment. Rather than substituting conventional methods, it seeks to provide an accessible preliminary evaluation mechanism, particularly in low-resource and humanitarian settings.
