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Deep learning-based classification of traditional Chinese medicine: a novel approach

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This analysis identifies Chinese herbal medicine accurately, suggesting potential in clinical applications.

The classification method achieved over 98% recognition accuracy for the entire dataset, demonstrating its effectiveness.
Utilizing the ResNet50 framework led to improved feature extraction and the construction of deeper networks.
The method recorded 100% accuracy for 13 herbs, showcasing its precision in categorizing complex samples.
This intelligent tool improves identification of traditional Chinese medicine, promoting advancements in personalized medicine.

Kang et al. (2025) studied this question.

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