Challenge Area:
Mental health in urban youth.

Problem Statement:
Rising mental health issues among urban youth are underdiagnosed due to stigma and limited access to screening.

Solution Concept:
Design an AI chatbot that uses natural language processing (NLP) to screen for mental health risks based on user conversations and provides guided self-help resources or referrals.

Expected Impact:
Screen 50,000 youth annually, connecting 10% to professional care.

Next Steps:
Train NLP models on anonymized mental health datasets, ensure privacy compliance, and pilot in schools.

Challenge Area:
Healthcare Accessibility

Problem Statement:
Rural communities lack timely detection of infectious diseases due to limited access to diagnostic facilities.

Solution Concept:
Create an AI-powered mobile app for preliminary disease diagnosis using symptom data and wearable sensor inputs, leveraging a gradient-boosted decision tree model for classification. The PoC ensures data preprocessing for noisy sensor data and includes edge-case handling for ambiguous symptoms.

Expected Impact:
Increases early detection rates by 30%, reducing disease spread in remote areas.

Next Steps:
Validate with medical datasets, integrate telemedicine APIs, and ensure HIPAA-compliant security.