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Tech Challenge

From enabling community-health workers to better serve patients in remote areas to helping governments in preventing deadly outbreaks, AI shows tremendous potential. Health Systems across the world face hindrances and glaring shortages of workers, medical equipment and other resources that need innovative approaches to overcome. AI shows great promise in not only optimizing existing resources and greatly enhancing healthcare delivery but also breaking the fundamental tradeoffs in health access, quality, and cost.
While the promise lies but it is accompanied by a dearth of proven and scalable solutions, with opaque barriers and a lack of an enabling environment for such innovations to scale.
The PHIXAI Tech Challenge aims to stimulate the ideation, development, and validation of AI-driven solutions in public health. By providing a platform for tech enthusiasts, startups, and innovators, it seeks to catalyze groundbreaking solutions with tangible impact on global health outcomes.

Vision and Objectives
Harnessing cutting-edge technologies and innovative solutions for developing AI enabled healthcare facilities. The objective of the challenge is to establish a dynamic platform that unites promising technologies, innovations, and solutions with key stakeholders in the field of AI and public health. These advancements and solutions fall into the following categories:
1. Product Innovations: Pioneering technological products designed to prevent, and diagnose diseases at individual or populational level, products which aid in treatment, treatment adherence, and more.
2. Process Innovations: Solutions encompassing data analysis tools, communication and information resources, information, and communication technology (ICT) solutions, supply chain optimization, standard operating procedures (SoPs), capacity-building, and mentoring solutions.

Thematic Areas
AI in Public Health Policy, and Planning:

  • Using AI to analyze multi-source data for evidence-based policy tools, AI dashboarding for decision making in healthcare delivery.
  • Optimizing surveillance, risk prediction, resource allocation, forecasting, needs assessment, targeting and selecting interventions, impact monitoring and evaluation for public health service delivery.
AI in Healthcare Professionals Assistance, and Community Engagement:
  • Developing AI tools to assist healthcare professionals in improved workflow efficiency, quality assurance, clinical decision-making, referrals, screening, and diagnostics.
  • Aid community health providers (including FLW) in virtual assistance for social and behavioral change, capacity building, reporting and records management, data driven diagnosis and care.
AI in Climate and Health:
    Environmental Health Monitoring:
  • AI-powered data analytics monitoring air quality and pollution patterns.
  • Assists in identifying vectors and other factors responsible for climate-related diseases.
  • Supports early warning systems for climate-related health risks.

  • Risk Mitigation/Management and Adaptation:
  • AI enabled climate modeling, predicting environmental changes affecting health.
  • Contributes to disease spread prediction influenced by one health / climate conditions.
  • AI aids in designing climate-resilient healthcare infrastructure.
  • Optimizes healthcare supply chains and ensures resource availability during climate events.
  • Innovative AI based technologies for participatory governance and planning to mitigate climate related health risks, strengthen community based early warning systems, surveillance mechanisms etc.

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