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marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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<b>The loss of insulin-positive cell clusters precedes the decrease of islet frequency and beta cell area in type 1 diabetes</b>
Published 2025“…Insulin-positive (INS+) single cells (≤10µm), cell clusters (>10 to <35µm), small- and medium-sized islets (35-100µm and 100-200µm) were significantly lost at type 1 diabetes onset, while large INS+ islets (>200µm) were preserved. Moreover, changes in endocrine composition also occurred in mAAb+ donors, including a significant decrease in the INS+ islet fraction. …”
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Image 7_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 6_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 3_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 1_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 2_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 4_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 5_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Image 8_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
Published 2025“…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …”
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Algorithm operation steps.
Published 2025“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”
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