Overview of the Cell2Spatial algorithm. حسب Huamei Li (8815955)

"…SC and spatial transcriptomics (ST) data were standardized using <i>SCTransform</i> in Seurat, with cell-type-specific genes identified through a modified entropy-based method (Step 1). …"

Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Control Parameters of IRSA Algorithm. حسب Wan-Hua Zhang (21601139)

"…This study focuses on this key area of diabetes prediction and aims to develop an innovative prediction method. Using the data set published by Kare, this paper constructs and compares various intelligent systems based on multilayer algorithms, and specifically introduces improved reptile search algorithm (IRSA) to optimize the weight and threshold initialization of traditional backpropagation (BP) neural networks. …"

Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms حسب Jie Zhu (126574)

"…Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression.…"

Example measurement and analysis units for landscape elements. حسب Jaewon Han (8660295)

الموضوعات:

Variables tested in the ML algorithms. حسب Gilson Yuuji Shimizu (19837946)

"…Data from Beth Israel Deaconess Medical Center (BIDMC), USA, were used for external validation. …"

Comparison of mass attenuation coefficient calculated by Geant4 simulation and acquired from NIST data. حسب Dong Hyeok Choi (12562048)

Research data. حسب Dominique Vincent-Genod (20552594)

الموضوعات:

Detailed information on software packages used for machine learning model development. حسب Jingru Dong (14076094)

الموضوعات:

Landslide susceptibility maps of the study area were developed using the RF algorithm for (a) post-Ketsana, (b) post-Podul, and (c) post-Molave periods. حسب Raja Das (1841107)

Characteristics of training algorithms. حسب Tuan Anh Nguyen (121944)

"…<div><p>Data training algorithms based on Artificial Intelligence (AI) often encounter overfitting, underfitting, or bias issues. …"

Algorithms runtime comparison. حسب Meilin Zhu (688698)

"…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …"

Data Sheet 1_An individualized risk prediction tool for ectopic pregnancy within the first 10 weeks of gestation based on machine learning algorithms.docx حسب Xin Du (208780)

"…A user-friendly web-based platform was developed for EP risk assessment based on this model. …"

Model-Based Clustering of Categorical Data Based on the Hamming Distance حسب Raffaele Argiento (647076)

"…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …"

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases حسب Jina Lee (3138492)

"…In this study, we developed a Python-based open-source algorithm compatible with the aqueous physical property models provided in the electrolyte templates of AspenTech software. …"