History of Process Transformation by de Wit Coetsee (21380672)

VLCC-States: Versioned Lineage-Driven Checkpointing of Composable States - Application to LLMs by Bogdan Nicolae (19418197)

Adjusted LASSO coefficients, Mexico 2022. by Oliver Mendoza-Cano (9148646)

List of data tables. by Mukhtar Ijaiya (18935122)

“…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …”

Flow chart of data source inclusion. by Mukhtar Ijaiya (18935122)

“…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …”

Predictive model-building process. by Mukhtar Ijaiya (18935122)

“…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …”

Comparison of models performance metrics. by Mukhtar Ijaiya (18935122)

“…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …”

Image 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.jpeg by Zhenze Zhang (22011422)

“…Predictors included demographics, comorbidities, laboratory parameters, vital signs, and disease severity scores. Missing data (<30%) were imputed using random forest. The cohort was split into training (75%) and internal testing (25%) sets, with hyperparameter optimization via 5-fold cross-validation. …”

Table 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.docx by Zhenze Zhang (22011422)

“…Predictors included demographics, comorbidities, laboratory parameters, vital signs, and disease severity scores. Missing data (<30%) were imputed using random forest. The cohort was split into training (75%) and internal testing (25%) sets, with hyperparameter optimization via 5-fold cross-validation. …”

Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants by Ahmed M. Alaa (5029781)

“…Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. …”

Data_Sheet_1_Fine-Scale Coral Connectivity Pathways in the Florida Reef Tract: Implications for Conservation and Restoration.PDF by Charles Frys (8803796)

Data_Sheet_2_Fine-Scale Coral Connectivity Pathways in the Florida Reef Tract: Implications for Conservation and Restoration.pdf by Charles Frys (8803796)