UCLA researchers recently developed the SLIViT, a new model of artificial intelligence (AI) that can analyze complex 3D medical scans with expert-level accuracy in a fraction of the time required by human experts.
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The details
- SLIViT (Slice Integration by Vision Transformer) can efficiently analyze various types of 3D images, including MRIs, CT scans, and ultrasounds.
- The model matches the accuracy of clinical experts, reducing analysis time by an impressive factor of 5.000.
- Unlike other AI models, SLIViT requires only hundreds of training samples, making it more practical for real-world applications.
- The framework utilizes transfer learning, using prior knowledge from 2D medical data for efficient training with smaller 3D datasets.
Why does it matter
With the growing demand for faster diagnostics, SLIViTâs ability to analyze images quickly and accurately offers game-changing potential for healthcare. The modelâs ability to work with small datasets also makes it more accessible to resource-constrained providers â potentially democratizing specialized medical imaging.
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