Exploring the determinants of anemia in young adult women (20-24 years): the role of AI-based interventions in health management.

Background: Anemia is a deficiency disorder in healthy red blood cells or hemoglobin is a widespread health concern among young adult women, effects considerable impact on physical health, productivity, and overall quality of life. Despite its high prevalence, effective diagnosis and management remain challenging due to the complex interaction of the causes, intensified by limited awareness and inadequate health concern behavior. Objective: The present study aimed to study the determinants of anemia and development of AI App for screening anemia and management particularly for young women. Methods: A total of 545 women aged 20-24 years were examined in the study. A structured questionnaire was designed to acquire socio-demographic characteristics and to assess dietary and lifestyle factors influencing the probability of anemia risk. Blood samples were collected to evaluate key hematological parameters. Furthermore, an AI (artificial intelligence)-based anemia risk assessment and mobile health intervention was developed and effectiveness of the tool was evaluated using machine learning models. Results: Mild anemia constituted the largest proportion of the study population (50.3%), followed by normal hemoglobin status (27.5%). The machine learning model accuracy was 74.39% and human data diagnostic accuracy of the AI-based anemia assessment system was found to be 71%, respectively. Conclusion: This digital health approach also aims to enhance anemia awareness, prevention, and management. Integrating AI into anemia care holds promise for delivering accurate, timely, and personalized interventions, particularly in resource-restricted settings, thereby improving health outcomes for young women and reducing the societal burden of anemia.