Advanced healthcare technology for early detection and intervention in child malnutrition
Comprehensive tools for malnutrition screening and management
Machine learning algorithms analyze anthropometric measurements to provide accurate malnutrition assessments.
Evaluates BMI, Weight-for-Length Z-scores, and MUAC to provide comprehensive nutritional status assessment.
Track child growth over time with visual charts and historical data analysis.
Fully compliant with World Health Organization growth standards and screening protocols.
Automatic notifications for high-risk cases requiring immediate intervention.
Automated clinical recommendations based on screening results and best practices.
Simple, fast, and accurate screening process
Enter basic information and guardian details
Record weight, height/length, and MUAC
Machine learning model evaluates risk
Receive diagnosis and recommendations