Effective connectivity analysis. by Akke Mats Houben (21572855)

Oscillatory Field Genesis: The Emergent Architecture of Spacetime, Matter, and Memory by Drippy Stone (21218843)

Data Sheet 1_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... by Ao Zhang (372387)

“…</p>Results<p>The results demonstrated that both the RF algorithm and excess green index (EXG) exhibited versatility in growth monitoring and yield prediction. …”

Data Sheet 2_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... by Ao Zhang (372387)

“…</p>Results<p>The results demonstrated that both the RF algorithm and excess green index (EXG) exhibited versatility in growth monitoring and yield prediction. …”

<b>Force-Position-Speed Planning and Roughness rediction for Robotic Polishing</b> by Ma Haohao (19780875)

“…The improved dung beetle optimization algorithm, back propagation neural network, finite element analysis and response surface method provide a strong guarantee for the selection of robotic polishing process parameters. …”

Single neurons in the human substantia nigra encode social learning signals by Arianna Davis (21370643)

“…Scripts for carrying out neural analyses are in the neural folder. Note you will also need to download the OSORT offline sorting algorithm, which is linked as a related work here and also cited in the paper.…”

Research on Olympic medal prediction based on GA-BP and logistic regression model Extended data by Sanglin Zhao (20599835)

“…</p><p dir="ltr">Method:</p><p dir="ltr">This article uses the GA-BP algorithm model, combined withgenetic algorithm (GA) and backpropagationneural network (BPNN),to optimize the weightsand bias parameters of the BP neural networkusing the global search capability of genetic algorithm, thereby improvingtraining efficiency and prediction performance.By estimating the number of Olympic gold medals and total medals, verifying the accuracy of the model, and predicting the medal table forthe 2028 Los Angeles Olympics. …”

Image 1_Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications.tif by Can Qi (540350)

“…Univariate Cox analysis and the LASSO algorithm were used to identify biomarkers for prognosis. …”

Table 3_Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications.xlsx by Can Qi (540350)

“…Univariate Cox analysis and the LASSO algorithm were used to identify biomarkers for prognosis. …”

Table 1_Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications.xlsx by Can Qi (540350)

“…Univariate Cox analysis and the LASSO algorithm were used to identify biomarkers for prognosis. …”

Table 2_Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications.xlsx by Can Qi (540350)

“…Univariate Cox analysis and the LASSO algorithm were used to identify biomarkers for prognosis. …”

Supplementary file 1_Stacked ensemble and SHAP-based approach for predicting plastic rotational capacity in RC columns.docx by Andrei-Odey Kadhim (22449631)

“…In this study, an extensive experimental database, comprising 258 rectangular and 151 circular RC column specimens, was compiled based on open data available and used to train machine learning models for predicting this parameter. Three algorithms, i.e. Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were implemented and optimized using grid search within a nested cross-validation framework. …”

Table 2_Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.xlsx by Jiachen Fan (21399268)

“…A protein-protein interaction (PPI) network was constructed, and key genes associated with both diseases were identified using Cytoscape software and machine learning algorithms. The correlation between immune cell infiltration and the two diseases was evaluated using the CIBERSORT algorithm. …”

Image 2_Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.tif by Jiachen Fan (21399268)

“…A protein-protein interaction (PPI) network was constructed, and key genes associated with both diseases were identified using Cytoscape software and machine learning algorithms. The correlation between immune cell infiltration and the two diseases was evaluated using the CIBERSORT algorithm. …”

Table 1_A multicentric real-world observational study to describe the use and efficacy of follitropin delta for IVF/ICSI procedures in patients at risk of hypo-response.docx by Anne-Claire Deloire (22222351)

“…The prescribed daily dose was usually based on the approved algorithm (N = 26; 74.3%) with a mean daily dose of 14.2 ± 4.1 mcg, resulting in a mean total dose of 187.7 ± 135.6 mcg. …”

Image 1_Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.tif by Jiachen Fan (21399268)

“…A protein-protein interaction (PPI) network was constructed, and key genes associated with both diseases were identified using Cytoscape software and machine learning algorithms. The correlation between immune cell infiltration and the two diseases was evaluated using the CIBERSORT algorithm. …”

Image 3_Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.tif by Jiachen Fan (21399268)

“…A protein-protein interaction (PPI) network was constructed, and key genes associated with both diseases were identified using Cytoscape software and machine learning algorithms. The correlation between immune cell infiltration and the two diseases was evaluated using the CIBERSORT algorithm. …”

Table 1_Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.docx by Jiachen Fan (21399268)

“…A protein-protein interaction (PPI) network was constructed, and key genes associated with both diseases were identified using Cytoscape software and machine learning algorithms. The correlation between immune cell infiltration and the two diseases was evaluated using the CIBERSORT algorithm. …”

In this paper, we use the term AI in its broadest sense. by Aidan Crilly (21743791)

“…<p>It thus covers a wide-ranging set of algorithms, including machine-learning and deep-learning techniques as subcategories, as illustrated here. …”

<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition by Qilin Li (535447)

“…It can accurately reflect the emotional changes of the human body by applying graphical-based algorithms or models. EEG signals are nonlinear signals. …”