The Ministry of Higher Education, Science, Research and Innovation has unveiled the Medical AI Data Platform—a centralised digital infrastructure that leverages artificial intelligence to accelerate medical diagnosis and reduce healthcare disparities.
The launch was announced by Minister Supamas Isarabhakdi during a recent seminar in Bangkok.
The platform houses over 2.2 million anonymised medical images across eight major disease categories: thoracic conditions, breast cancer, eye diseases, abdominal issues, skin diseases, strokes, osteoporosis, and other bone-related disorders.
These images are used to train AI models that assist doctors in making diagnoses, particularly in areas with limited medical resources.
Currently, the Medical AI Consortium comprises six partners: the Department of Medical Services; the Faculty of Medicine, Ramathibodi Hospital, Mahidol University; the Faculty of Medicine, Chulalongkorn University; the Faculty of Medicine, Prince of Songkla University; the Faculty of Medicine, Chiang Mai University; and the Faculty of Medicine, Vajira Hospital, Navamindradhiraj University.
Ms Supamas stated that the ministry encourages more medical institutions, universities, and researchers to join the AI ecosystem to further strengthen Thailand’s healthcare system.
“This platform is not just a data bank—it lays the foundation for practical, scalable AI innovations in Thai healthcare,” said Ms Supamas.
The system was developed by the National Electronics and Computer Technology Centre (Nectec), a unit under the National Science and Technology Development Agency (NSTDA), and complies with national standards for data security and cloud systems, said NSTDA director Prof Sukit Limpijumnong.
It is designed to support every stage of medical AI development in a secure, standardised, and efficient manner. The platform complies with Government Data Centre and Cloud (GDCC) standards and is overseen by the Department of Medical Services under the Ministry of Public Health, he added.
The platform features three main components. The first is data management, supported by RadiiView—a software and cloud-based application developed by Nectec researchers for medical image annotation.
This tool enables doctors to precisely mark critical image features, generating high-quality datasets for AI training.
The second component is AI modelling, facilitated through the NomadML platform, which allows researchers to develop and refine AI models.
Annotated datasets from RadiiView can be directly applied within this system, which is integrated with NSTDA’s supercomputer to accelerate processing and model training.
The third component is AI service deployment, which delivers validated AI models for real-world use in clinical settings.
