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.