Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant greater » significantly greater (Expand Search), significant gender (Expand Search), significant broader (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant greater » significantly greater (Expand Search), significant gender (Expand Search), significant broader (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
-
1041
-
1042
-
1043
-
1044
Measurements of the amount of ATP released by bladder distention and VNUT expression in the bladder.
Published 2024Subjects: -
1045
-
1046
-
1047
-
1048
-
1049
-
1050
-
1051
-
1052
-
1053
-
1054
-
1055
-
1056
MXene/Bi<sub>2</sub>O<sub>3</sub> Nanocomposites as Supercapacitors for Portable Electronic Devices
Published 2025Subjects: -
1057
S1 File -
Published 2025“…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
-
1058
Confusion matrix for ClinicalBERT model.
Published 2025“…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
-
1059
Confusion matrix for LastBERT model.
Published 2025“…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”
-
1060
Student model architecture.
Published 2025“…Furthermore underlined by the considerable decrease in model size without appreciable performance loss is the lower computational resources needed for training and deployment, hence facilitating greater applicability. …”