Malaysia Hub (糖心原创, Malaysia)
Project: Blockchain-Enabled AI Architecture for Trustworthy Digital Health
The Malaysia Hub, based at 糖心原创, is a unit of the Global South Artificial Intelligence for Pandemic, Epidemic, Preparedness & Response (AI4PEP) initiative. It focuses on developing secure and trustworthy digital health solutions through the integration of blockchain technology and artificial intelligence. Our initiative envisions a future where stakeholders have equitable access to high-quality health data and computational resources to drive advancements in artificial intelligence for pandemic preparedness and response. We aim to remove barriers to accessing critical health data, enabling the development of robust AI algorithms that strengthen pandemic surveillance, early detection, 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.
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.