A robust model training strategy using hard negative mining in a weakly labeled dataset for lymphatic invasion in gastric cancer
Abstract Gastric cancer is a significant public health concern, emphasizing the need for accurate evaluation of lymphatic invasion (LI) for determining prognosis and treatment options. However, this task is time‐consuming, labor‐intensive, and prone to intra‐ and interobserver variability. Furthermo...
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| Main Authors: | , , , , |
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| Format: | Book |
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Wiley,
2024-01-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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