Summary of All-in-one Platform For Ai R&d in Medical Imaging, Encompassing Data Collection, Selection, Annotation, and Pre-processing, by Changhee Han et al.
All-in-one platform for AI R&D in medical imaging, encompassing data collection, selection, annotation, and pre-processing
by Changhee Han, Kyohei Shibano, Wataru Ozaki, Keishiro Osaki, Takafumi Haraguchi, Daisuke Hirahara, Shumon Kimura, Yasuyuki Kobayashi, Gento Mogi
First submitted to arxiv on: 10 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper addresses the limitations of medical imaging research and development by establishing a commercial platform for collecting, processing, and providing datasets for artificial intelligence/machine learning-based devices. The challenges highlighted are significant data imbalance, with most data from Europe/America, and the need for substantial time and investment to curate proprietary datasets. To address these issues, the authors focus on harnessing under-represented data from Japan and broader Asia, including Computed Tomography, Magnetic Resonance Imaging, and Whole Slide Imaging scans. The platform aims to provide ready-to-use datasets for medical AI R&D by offering them to AI firms, biopharma, and medical device makers and using them as training/test data to develop tailored AI solutions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper solves a big problem in medical imaging research. Right now, most of the data used to train artificial intelligence is from Europe or America, which isn’t very representative of the world’s population. The authors are creating a platform that collects and processes data from Japan and other parts of Asia, where 60% of the world’s population lives. This will help make AI systems better at recognizing diseases in people from these regions. They’re also working on making sure this data is secure by using blockchain technology. |
Keywords
» Artificial intelligence » Machine learning
