NUTRIS

Inspiration

Malnutrition among children is a significant public health challenge, with long-term effects on education, physical growth, and cognitive development. This project was inspired by the need to address malnutrition risks using a common sense based reasoning approach to provide targeted and actionable recommendations for improving child health outcomes.

What it does

Assesses the nutritional health of children by analyzing factors like body measurements, symptoms, socio-economic background, diet, and lifestyle. Classifies children into malnutrition categories, such as normal, mild, moderate and severe. Provides dietary recommendations and interventions, including breastfeeding guidance, supplementary feeding, sanitation improvements, and medical consultations. Uses additional data on dietary intake, activity levels, and micronutrient deficiencies to recommend healthcare services and government programs.

How we built it

Conducted research to identify key malnutrition indicators such as BMI, growth standards, caloric intake, and nutrient deficiencies. Developed logical rules using Prolog and s(CASP), leveraging datasets on children’s height, weight, activity, and socio-economic status. Integrated data from multiple sources, including food intake and lifestyle information, to create a comprehensive assessment system. Linked malnutrition risk assessments to actionable recommendations involving medical, social, and governmental resources.

Challenges we ran into

Complexity of Factors: Integrating multiple factors such as growth, activity, and socio-economic conditions into a cohesive system. Inconsistent Data: Limited and regionally inconsistent data on malnutrition indicators posed challenges in creating a universal model. Debugging Prolog Rules: Ensuring the Prolog rules provided accurate classifications and recommendations, especially with recursive rules. Intervention Definition: Tailoring specific interventions for children’s unique needs required an integrated healthcare and social resource approach.

Accomplishments that we're proud of

Successfully built a logical system using Prolog to assess nutritional health and provide targeted interventions. Designed customizable recommendations that adapt to real-time inputs, making the system flexible and user-focused. Effectively integrated data on growth, socio-economic status, and nutrition to create a holistic health profile. Achieved accurate classification of malnutrition levels (severe, moderate, mild, or normal) with actionable insights for caregivers.

What we learned

Learned to leverage s(CASP) for complex health assessments and logical reasoning. Gained an understanding of the importance of a holistic approach to health, integrating diet, growth, and socio-economic factors. Recognized the potential for health solutions to make a tangible impact on the well-being of children and families.

What's next for NUTRIS

Integrating a chatbot into our solution to make it interactive to use for the end user. Expanding the scope of the solution to recommend a nutrition plan based on the dietary habits and health status of the user. To customize the tool based on regional factors.

Built With

• prolog
• scasp