Search alternatives:
algorithm machine » algorithm achieves (Expand Search)
machine function » achieve functions (Expand Search), sine function (Expand Search)
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
algorithm machine » algorithm achieves (Expand Search)
machine function » achieve functions (Expand Search), sine function (Expand Search)
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
-
61
-
62
-
63
-
64
-
65
-
66
-
67
-
68
-
69
Automatic translation error detection based on fuzzy decision tree algorithm.
Published 2025Subjects: -
70
Table 8_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
71
Table 9_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
72
Table 4_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
73
Table 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
74
Image 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.tif
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
75
Table 3_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
76
Table 7_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
77
Table 10_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
78
Image 2_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.tif
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
79
Table 5_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”
-
80
Image 3_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.tif
Published 2025“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”