A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</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). …”

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

“…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”

Table_3_Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species.docx by Laura M. Zingaretti (8409285)

“…However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. …”

Table_2_Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species.docx by Laura M. Zingaretti (8409285)

“…However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. …”

Image_1_Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species.pdf by Laura M. Zingaretti (8409285)

“…However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. …”

Table_1_Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species.docx by Laura M. Zingaretti (8409285)

“…However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. …”

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... by Uttam Khatri (12689072)

“…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. …”