The problem Smart Health AI solves

• Overburdened Healthcare System: Provides early diagnosis and health management tools to reduce patient load on healthcare facilities.
• Lack of Personalized Patient Care: Offers tailored health recommendations and management plans based on individual data.
• Diagnostic Errors Due to Incomplete Information: Integrates comprehensive patient data from clinical texts, images, and lab reports for accurate diagnosis.
• High Healthcare Costs: Delivers accessible and cost-effective AI-driven health services, reducing the need for expensive consultations.
• Delayed Diagnosis: Encourages early detection of health issues, promoting timely medical intervention.
• Patient Ignorance Due to Inconvenience:Makes health assessment and management convenient, encouraging patients to seek help without hospital visits

Challenges we ran into

• Integration with External APIs: Seamlessly integrating with external APIs, like Edamam, for nutritional analysis and maintaining data consistency.
• Response Relevance: Generating responses that are not only accurate but also contextually relevant to the user's query and medical context.