Enhancing Recommendations Using an Intelligent System for Mothers to Combat Intestinal Parasitic Infections

Area of Science:

• Public Health
• Artificial Intelligence
• Parasitology

Background:

• Intestinal parasitic infections are a major global health issue, especially in developing nations.
• These infections cause significant morbidity and mortality worldwide.
• Artificial intelligence offers potential for personalized therapeutic recommendations.

Purpose of the Study:

• To develop an intelligent system for mothers to recommend effective interventions against intestinal parasitic infections.
• To leverage AI for tailored, culturally relevant advice on preventing parasitic infections.
• To enhance mothers' knowledge and adoption of preventive measures.

Main Methods:

• A quasi-experimental (pre/post-test) design was used with 200 mothers in Cairo, Egypt.
• Data collected via a structured knowledge questionnaire and a preventive measures checklist.
• Integrated K-Means clustering, GPT-4o large language models, and prompt engineering for tailored recommendations.

Main Results:

• Significant improvements in mothers' knowledge and preventive measures post-intervention.
• A strong positive correlation found between knowledge levels and preventive actions.
• AI-driven insights and tailored treatments positively impacted mothers' hygiene practices.

Conclusions:

• Preventive educational programs, enhanced by AI, significantly improve mothers' knowledge and practices.
• AI and large language models are crucial for generating personalized recommendations to improve hygiene.
• This study highlights the effectiveness of AI in combating intestinal parasitic infections through tailored interventions.