The confidence curve of a binary image. by Dingming Yang (8505990)

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

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

“…To address this, the research integrates a modified A* pathfinding algorithm with a U-Net convolutional neural network, a custom statistical binary classification method, and a personalized Min-Max connectivity threshold to automate the detection of astrocyte connectivity.…”

Overview of CINner’s mathematical model and simulation algorithm. by Khanh N. Dinh (20549532)

Summary of the calibration process. by Kenneth Y. Wertheim (11226486)

Sequence of events in one realisation of the stochastic process. by Kenneth Y. Wertheim (11226486)

Turnover Dependent Phenotypic Simulation: A Quantitative Constraint-Based Simulation Method That Accommodates All Main Strain Design Strategies by Rui Pereira (187696)

“…Here, we present a constraint-based algorithm, the turnover dependent phenotypic simulation (TDPS) that quantitatively simulates phenotypes in a resource conscious manner. …”

ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …”

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Hierarchical clustering based on the gene-expression data of three brain regions. by Souvik Seal (12437166)

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Normality assessment through Anderson-Darling test on sample distribution based on TCGA pan-cancer atlas across genes. by Yi-Wen Hsiao (13767916)

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DE genes detected by different DEA algorithms. by Jie Xue (417504)

“…Our findings suggest that DEA algorithms extended from bulk RNA-seq are still competitive under small biological replicate conditions, whereas the newly developed method DEF-scRNA-seq which is based on information entropy offers significant advantages. …”

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

Summary statistics of the gene expression profile of 9,835 samples in TCGA pan-cancer atlas. by Yi-Wen Hsiao (13767916)

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Performance of our proposed method in four scenarios (I to IV) using naïve simulated data with the complete version. by Yi-Wen Hsiao (13767916)

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Comparison of run-time for simulations with three and four conditions. by Souvik Seal (12437166)

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Comparison of edge detection performance for simulations with four conditions. by Souvik Seal (12437166)

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Comparison of edge detection performance for simulations with three conditions. by Souvik Seal (12437166)

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Comparison of edge-weight estimation performance for simulations with three conditions. by Souvik Seal (12437166)

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