Search alternatives:
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data stress » data streams (Expand Search)
data path » data data (Expand Search), data part (Expand Search)
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data stress » data streams (Expand Search)
data path » data data (Expand Search), data part (Expand Search)
-
1
A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”
-
2
PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
-
3
-
4
-
5
Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
-
6
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”