Search alternatives:
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
were optimization » before optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
binary mask » binary image (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
mask dose » last dose (Expand Search), risk dose (Expand Search)
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
were optimization » before optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
binary mask » binary image (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
mask dose » last dose (Expand Search), risk dose (Expand Search)
-
1
Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
Published 2022“…In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. …”
-
2
A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …”
-
3
Datasets and their properties.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
-
4
Parameter settings.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
-
5
Flow diagram of the proposed model.
Published 2025“…Clinical, demographic, and supplement variables were preprocessed into 21 predictors. Four algorithms (K-Nearest Neighbors, Classification and Regression Tree, Support Vector Machine, and Random Forest) were implemented alongside their LR–ABC hybrid counterparts. …”
-
6
Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
Published 2021“…This study is devoted to develop a quantitative structure–property relationship model for predicting the <i>T</i><sub>d</sub>,<sub>5%onset</sub> of binary imidazolium IL mixtures. Both in silico design and data analysis descriptors and norm index were employed to encode the structural characteristics of binary IL mixtures. …”
-
7
DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf
Published 2022“…Together with Raman spectra of 59 Streptococcus patient isolates, they were used to train and optimize binary classification models (PLS-DA). …”
-
8
-
9
-
10
-
11
-
12
-
13
-
14
-
15
-
16
-
17
-
18
-
19
-
20