بدائل البحث:
complement ipca » complement 5a (توسيع البحث), complement c3 (توسيع البحث), complement c5 (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
ipca algorithm » wgcna algorithm (توسيع البحث), cscap algorithm (توسيع البحث), ii algorithm (توسيع البحث)
level finding » novel findings (توسيع البحث), review finding (توسيع البحث), level coding (توسيع البحث)
complement ipca » complement 5a (توسيع البحث), complement c3 (توسيع البحث), complement c5 (توسيع البحث)
data algorithm » data algorithms (توسيع البحث), update algorithm (توسيع البحث), atlas algorithm (توسيع البحث)
ipca algorithm » wgcna algorithm (توسيع البحث), cscap algorithm (توسيع البحث), ii algorithm (توسيع البحث)
level finding » novel findings (توسيع البحث), review finding (توسيع البحث), level coding (توسيع البحث)
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The schematic diagram of the hierarchical clustering algorithm.
منشور في 2025الموضوعات: "…original multidimensional data…"
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A schematic diagram of the settlement spatial distribution model based on factor analysis integrated with the hierarchical clustering algorithm.
منشور في 2025الموضوعات: "…original multidimensional data…"
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The silhouette coefficient scores for different algorithms at various levels.
منشور في 2025الموضوعات: "…original multidimensional data…"
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Data Sheet 1_Decoding the association between health level and human settlements environment: a machine learning-driven provincial analysis in China.zip
منشور في 2025"…</p>Methods<p>Using panel data from 31 Chinese provinces spanning 2012 to 2022, a composite Health Level Index (HLI) was constructed based on four core health indicators using the Entropy-TOPSIS method. 19 HSE indicators covering five dimensions—ecological environment, living environment, infrastructure, public services, and sustainable environment—were selected as explanatory variables. …"
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Data Sheet 1_Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs.pdf
منشور في 2025"…</p>Results<p>In the internal validation, the Lung Abnormality and Tuberculosis models achieved an AUC of 0.94, while the Radiological Findings model yielded a mean AUC of 0.84. During the external validation, utilizing the ground truth generated by board-certified thoracic radiologists, the algorithm achieved better sensitivity in 6 out of 11 classes than physicians with varying experience levels. …"
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