Inferred phylogenies for POP66. by Henri Schmidt (17364844)

Runtime analysis for B-ALL patient phylogenies. by Henri Schmidt (17364844)

ARI and NMI of inferring mutation clusters. by Henri Schmidt (17364844)

Inferred phylogenies for CSC28. by Henri Schmidt (17364844)

<i>ℓ</i>₁ matrix error for B-ALL patient phylogenies. by Henri Schmidt (17364844)

Numerical Simulation and Machine Learning-Driven Engineering of K₂GeI₆ Perovskite Solar Cells for High-Efficiency and Sustainable Photovoltaics by Md. Tarekuzzaman (21793271)

“…Seven algorithmsLinear Regression, Ridge, Lasso, Random Forest, Gradient Boosting, Support Vector Regression (SVR), and Multilayer Perceptron (MLP)were evaluated. …”

Analysis flowchart. by Haoran Zhang (731854)

“…This comprehensive model comparison provides a broader perspective for determining the optimal model for liver fat diagnosis. It was found that the 2D radiomics models based on the random forest and Bagging decision tree algorithms show high consistency with the QCT-based classification diagnosis of fatty liver used by experienced radiologists.…”

Participant flow chart. by Haoran Zhang (731854)

“…This comprehensive model comparison provides a broader perspective for determining the optimal model for liver fat diagnosis. It was found that the 2D radiomics models based on the random forest and Bagging decision tree algorithms show high consistency with the QCT-based classification diagnosis of fatty liver used by experienced radiologists.…”

Feature weighting. by Haoran Zhang (731854)

“…This comprehensive model comparison provides a broader perspective for determining the optimal model for liver fat diagnosis. It was found that the 2D radiomics models based on the random forest and Bagging decision tree algorithms show high consistency with the QCT-based classification diagnosis of fatty liver used by experienced radiologists.…”

S1 File - The critical effects of self-management strategies on predicting cancer survivors’ future quality of life and health status using machine learning techniques by Ju Youn Jung (22139209)

“…Representative Samples: HealthingU Web-Based Survey and Patient Report. S2 Table. XGBoost Model’s Optimized Hyperparameters for Global QoL Prediction. …”

Ultralong-Range Sensing of Non-Contact Triboelectric Nanogenerator via Synergistic Design of Porous Microspheres and High Dielectric Properties by Shenzhuo Zhang (20960274)

“…In addition, with deep learning algorithms optimizing recognition, the system can accurately distinguish multiple human dynamic behaviors, such as walking, running, and jumping, within the aforementioned distances. …”

Ultralong-Range Sensing of Non-Contact Triboelectric Nanogenerator via Synergistic Design of Porous Microspheres and High Dielectric Properties by Shenzhuo Zhang (20960274)

“…In addition, with deep learning algorithms optimizing recognition, the system can accurately distinguish multiple human dynamic behaviors, such as walking, running, and jumping, within the aforementioned distances. …”

The study flowchart. by Nguyen Tat Thanh (10296398)

“…At admission, LAR demonstrated superior discriminatory ability (AUC: 0.82; 95% CI: 0.76–0.87) compared to serum lactate (AUC: 0.72; 95% CI: 0.65–0.78) and LB ratio (AUC: 0.68; 95% CI: 0.62–0.74) (all p < 0.001). The Youden-index based optimal LAR cutoff was 1.25, whereas that for the LB ratio was 0.20. …”

Missing value chart of candidate variables. by Nguyen Tat Thanh (10296398)

“…At admission, LAR demonstrated superior discriminatory ability (AUC: 0.82; 95% CI: 0.76–0.87) compared to serum lactate (AUC: 0.72; 95% CI: 0.65–0.78) and LB ratio (AUC: 0.68; 95% CI: 0.62–0.74) (all p < 0.001). The Youden-index based optimal LAR cutoff was 1.25, whereas that for the LB ratio was 0.20. …”

YOLO11 network architecture. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”

Heatmap comparison on SSDD dataset. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”

Dataset specifications. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”

CCFM module architecture. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”

IoU and MPDIoU as bounding box losses. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”

Model complexity comparison in ablation study. by Rui He (824726)

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”