An Overview
Global South Artificial Intelligence for Pandemic, Epidemic, Preparedness & Response (AI4PEP)
Our initiative envisions a future where stakeholders have unrestricted access to high-quality health data and computational resources to drive advancements in artificial intelligence (AI) for pandemic control and preparedness. With support from the Sunway Group and guided by evidence-based research, we have developed the PCMR Dataset Index, a web-based resource that aggregates AI-ready datasets tailored for pandemic management. We aim to dismantle barriers to accessing critical health data, facilitating the development of AI algorithms that enhance pandemic surveillance and response efforts.
Mission
Our mission is to revolutionise pandemic and epidemic preparedness and response efforts by integrating cutting-edge technologies such as Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT). Through interdisciplinary collaboration and sustained international research, we aim to develop a specialist solution that ensures the secure, accurate, and privacy-preserving management of health data. By harnessing the power of AI for data analysis, Blockchain for secure data management, and IoT for real-time data gathering, our comprehensive system will enable more efficient decision-making and proactive measures to control disease spread. Our mission extends beyond borders as we strive to contribute to global health outcomes by leveraging the project's results and innovations on an international scale."
Vision
We believe that responsible utilisation of anonymised clinical data for pandemic control is imperative for global health security. This vision has prompted initiatives to share anonymised medical data for collaborative research and public health efforts. As advocates for open science and equitable access to data, we strive to promote the sharing of well-curated, de-identified clinical datasets to accelerate AI development for pandemic preparedness. Through the PCMR Dataset Index, we aim to facilitate collaboration and innovation in the fight against pandemics worldwide.
Context
The proliferation of digital healthcare data globally presents an unprecedented opportunity to improve pandemic control measures and reduce the impact of outbreaks. However, challenges such as data silos and proprietary ownership hinder the equitable and transparent development of AI solutions for pandemic preparedness.
Motivation
There is growing recognition of the limitations of existing pandemic response strategies, necessitating innovative approaches such as AI-driven solutions. However, available datasets often lack the diversity and detailed annotations required for effective machine learning in pandemic scenarios. As a result, there is an urgent need to curate high-quality datasets that meet the criteria for being "AI-ready" to support generalised machine learning research for pandemic control.
