History of Process Transformation by de Wit Coetsee (21380672)

Fig 3 - by Ali Ahmed (2567584)

An example of a type of texture of binary preferred/non-preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

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)

Latent state estimations for experimental data with no stressors for subject 3. by Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 3. by Samiul Alam (18563323)

List of data tables. by Mukhtar Ijaiya (18935122)

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

Latent state estimations for experimental data with time limit for subject 3. by Samiul Alam (18563323)

An example of a type of a percent cover of preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

An example of a type of percent cover of preferred ranges of vegetation index texture values type feature. by Elise Varaela Voltura (17592996)

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. …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

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. …”

MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

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. …”