KEYWORDS: Artificial intelligence, Medical imaging, Blockchain, Education and training, Medical device development, Computed tomography, Magnetic resonance imaging, Medical research, Deep learning, Pathology
Deep Learning is advancing medical imaging Research and Development (R&D), leading to the frequent clinical use of Artificial Intelligence/Machine Learning (AI/ML)-based medical devices. However, to advance AI R&D, two challenges arise: 1) significant data imbalance, with most data from Europe/America and under 10% from Asia, despite its 60% global population share; and 2) hefty time and investment needed to curate proprietary datasets for commercial use. In response, we established the first commercial medical imaging platform, encompassing steps like: 1) data collection, 2) data selection, 3) annotation, and 4) pre-processing. Moreover, we focus on harnessing under-represented data from Japan and broader Asia. We are preparing/providing ready-to-use datasets for medical AI R&D by 1) offering these datasets to companies and 2) using them as additional training data to develop tailored AI solutions. We also aim to merge Blockchain for data security and plan to synthesize rare disease data via generative AI.
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