Search alternatives:
significantly improve » significantly improved (Expand Search)
improve decrease » improve disease (Expand Search), improved urease (Expand Search), improves disease (Expand Search)
higher decrease » higher degree (Expand Search), higher degrees (Expand Search), highest increase (Expand Search)
significantly improve » significantly improved (Expand Search)
improve decrease » improve disease (Expand Search), improved urease (Expand Search), improves disease (Expand Search)
higher decrease » higher degree (Expand Search), higher degrees (Expand Search), highest increase (Expand Search)
-
221
Image 2_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif
Published 2025“…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
-
222
Image 4_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif
Published 2025“…Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”
-
223
Recruitment flow diagram of the current study.
Published 2025“…In phase 2, EQ-5D-5L summary improved most in participants with higher education levels and longer recovery expectations; EQ-VAS improved most in cyclists and patients with longer recovery expectations.…”
-
224
-
225
-
226
-
227
-
228
Data.
Published 2025“…However, the reported rate of urticaria decreased significantly in post-LAW period(P = 0.043). …”
-
229
Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
-
230
Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
-
231
Improved model distillation structure.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
-
232
-
233
-
234
-
235
-
236
-
237
-
238
-
239
-
240