Evaluating Child Malnutrition Using Artificial Intelligence in Developing Countries (Case Study in India: NutriAl)

Background and Objective: Malnutrition in infants and young children is a significant public health concern, especially in developing countries with limited resources. Millions of children worldwide suffer from malnutrition and its complications. Despite the best efforts of governments and organizations, malnutrition persists as one of the leading causes of illness and death among children under five. Physical measurements, such as weight, height, head circumference, and mid-upper arm circumference (MUAC), are commonly used to assess the nutritional status of children. However, these methods require resources and can be challenging to implement on a large scale. This research aims to develop and identify an artificial intelligence tool, utilizing a research sample from India. NutriAl is a low-cost solution that employs a small sample classification approach to identify malnutrition by analyzing two-dimensional images of subjects in various conditions. In summary, this article focuses on developing an AI-based system for assessing malnutrition in children. Materials and Methods: This study employs a descriptive-analytical method. All available sources were reviewed and data were extracted for various sections of the research. Findings: Preliminary results indicate that novel deep learning approaches can assist in identifying malnutrition through identified indicators resulting from variations in age, gender, physical characteristics, and more. Conclusion: The anticipated outcomes of this research include examining the feasibility of using two-dimensional images obtained from smart cameras for health screening without additional sensors or training. The development of a continuous growth monitoring system based on the proposed model and the digitization of health parameters and records for better data management are also expected.

کلیدواژه ها:

Artificial Intelligence ، Deep Learning ، Malnutrition ، Child