The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

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. …”

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. by Danish M. Anwer (15383441)

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

S1 Data - by Ali Akbar Moosavi (17769033)

“…Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf by Marcel Dahms (9160118)

Diversity and specificity of lipid patterns in basal soil food web resources by Jakob Kühn (7288466)

“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…<p dir="ltr">NanoDB is a Python-based application developed to optimize the management of experimental data in research settings. …”

Table_1_EZcalcium: Open-Source Toolbox for Analysis of Calcium Imaging Data.DOCX by Daniel A. Cantu (5543519)

“…For decades, the only way to perform these analyses was for individual laboratories to write their custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. …”

Data_Sheet_1_Degenerate Beta autoregressive model for proportion time-series with zeros or ones: An application to antimicrobial resistance rate using R shiny app.PDF by Jevitha Lobo (14368401)

“…The estimation is done using maximum likelihood with a non-linear optimization algorithm. An R shiny app has been provided for the same.…”

Data_Sheet_1_Degenerate Beta autoregressive model for proportion time-series with zeros or ones: An application to antimicrobial resistance rate using R shiny app.PDF by Jevitha Lobo (14368401)

“…The estimation is done using maximum likelihood with a non-linear optimization algorithm. An R shiny app has been provided for the same.…”

Data_Sheet_1_Constructing machine learning models based on non-contrast CT radiomics to predict hemorrhagic transformation after stoke: a two-center study.docx by Yue Zhang (30585)

Table_1_The Machine Learning Model for Distinguishing Pathological Subtypes of Non-Small Cell Lung Cancer.xlsx by Hongyue Zhao (3205191)

“…</p>Results<p>Boruta algorithm selected the optimal subset consisting of 13 features, including two clinical features, two laboratory indicators, and nine PEF/CT radiomic features. …”

Comparative analysis of clinical characteristics between ovarian cancer and ovarian cyst patients by Li (20568581)

“…<p dir="ltr">We collected preoperative CA125, HE4 data, and other clinical characteristics from 192 Chinese patients with ovarian cysts and 188 patients with ovarian cancer, including family history, reproductive history, age at menarche, and menopausal status, as well as postoperative pathological staging information for ovarian cancer patients. …”

Image_1_Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation.tif by Qi Wang (22418)

“…</p>Methods<p>To this end, this study, by utilizing the transcriptomic as well as single cell data and integrating 20 mainstream machine-learning (ML) algorithms. …”