Identification of PRG molecular subtypes and prognostic outcome analysis. by Xiangxin Wu (22320058)

Integration of datasets. by Meili Liu (327309)

This figure highlights the limitations of manual scoring. by Saeed Mohammadzadeh (13492285)

Application of explainable clustering on cell features for unsupervised organization scoring. by Saeed Mohammadzadeh (13492285)

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

Table 1_Identification of prognostic hub genes and functional role of BAIAP2L2 in prostate cancer progression: a transcriptomic and experimental study.xlsx by Xiangyang Zhan (10968681)

“…Background<p>Prostate cancer (PCa) is a prevalent malignancy in men, and understanding its molecular mechanisms is crucial for identifying therapeutic targets.…”

GSVA, GO, and KEGG Enrichment Analysis After Sample Clustering and Subtyping. by Ziyang Liu (242055)

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”

SpatialKNifeY analysis landscape. by Shunsuke A. Sakai (13789939)

Average trace of each ROI cluster at maximum silhouette score. by Virgil Christian Garcia Castillo (19688355)

Table 1_Neural network-based performance prediction of marine UHPC with coarse aggregates.pdf by Yunhao Luan (20800046)

Grid search process. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Research framework. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Parameter configuration for TextCNN model. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Model performance on the validation set. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Performance comparison of different models. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Performance evaluation of models on test dataset. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Topic classification based on KeyBERT-TextCNN. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Summary of perceived risk dimensions. by Lin Qi (128224)

“…Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Data for "A multi-objective platform for autonomous property targeting and optimization of colloidal lead halide perovskite quantum dots" by Neal Munyebvu (19690954)