Healthcare AI developer VinBrain has announced a new partnership with Stanford University to enhance AI medical imaging.
To design a state-of-the-art AI-enabled platform for more accurate diagnosis and treatments, a tremendous amount of geographically distributed data, medical images, and patient medical records are required for system training.
The Data Use Agreement (DUA) grants Stanford University and VinBrain the collaborative power to improve efficiency in radiology reports and advance AI in healthcare by sharing relevant de-identified data for model training and testing, while tackling complexity, ambiguity, and limitations in medical image interpretation.
Starting with 240,000 anonymized medical images and report pairs provided by Stanford through this DUA, VinBrain will work to improve the accuracy of the RadGraph method through a research collaboration with Stanford to extract clinical entities and relation annotations from a large dataset of full-text radiology reports.
With this strong support from Stanford, VinBrain aims to raise the bar for research on AI solutions by collaborating beyond Vietnam to improve product quality, meanwhile, continuing to add and develop the most massive data source in Vietnam to date, with more than 2.3 million images being analyzed through the DrAid platform so far.
Earlier in January, VinBrain had also announced a partnership with Microsoft to focus on three areas of healthcare AI: data sharing, cross-product validation, and R&D. As part of the deal, Microsoft Azure will be used to facilitate the sharing of millions of data on DrAid while ensuring its privacy and security, data governance, and regulatory compliance. They will also use Azure Cognitive Services for Computer Vision to develop VinBrain's AI capability for processing and returning images and building image classifiers.
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