Two-dimensional visualization of cell clustering in the Pollen dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Two-dimensional visualization of cell clustering in the Petropoulos dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Two-dimensional visualization of cell clustering in the Guo2 dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Two-dimensional visualization of cell clustering in the iPSC dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Two-dimensional visualization of cell clustering in the CellType dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Multiple collinearity diagnosis results. by Peiwen Zhang (1863202)

An illustration of the Deepwalk algorithm operation involves a random walk on the graph, resulting in a “walk” sequence, which is then utilized to construct a graph. by Xiaobing Deng (1622233)

Normalized convergence time. by Song Qian (5031221)

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”

VGR structure. by Song Qian (5031221)

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”

Comparison of normalized throughput and load. by Song Qian (5031221)

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”

Principle of transfer learning. by Song Qian (5031221)

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”

Body-connected routing scenario. by Song Qian (5031221)

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”

Identification and validation of hub DE-podos in bulk RNA-seq. by Hailin Li (453832)

Block structure location in the Yueman area. by Chen Ma (714759)

“…Seismic attributes that were sensitive to different types of strike-slip faults were selected, and multiple attributes were merged to obtain a fracture distribution map using the best surface voting algorithm. …”

Benchmarking results under a 60% dropout rate. by Siyi Huang (8562174)

Cell clustering in Siletti dataset before and after imputation. by Siyi Huang (8562174)

Supplementary file 1_Multimodal framework for phishing attack detection and mitigation through behavior analysis using EM-BERT and SPCA-BASED EAI-SC-LSTM.docx by Mahmoud Murhej (21676118)

“…Then, by utilizing Spherical Principal Component Analysis (SPCA), the features are extracted. Further, the optimal features are chosen by using the Cauchy distribution-based Seagull Optimization Algorithm (CSOA). …”

Table 1_An interpreting machine learning models to predict amputation risk in patients with diabetic foot ulcers: a multi-center study.doc by Haoran Tao (8466261)

“…Data from 297 patients across multiple tertiary centers were used for external validation. …”

Image 1_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.tif by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”

Image 8_Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.png by Chuanyu Ma (6701108)

“…The ITH-score of PRAD samples was evaluated using the DEPTH algorithm. The optimal cut-off value of RiskScore was calculated based on the difference in survival curves, and PRAD patients were classified into high ITH and low ITH groups based on the optimal cut-off value. …”