Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Fig 2 - by Olaide N. Oyelade (14047002)

An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... by Olaide N. Oyelade (14047002)

An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... by Olaide N. Oyelade (14047002)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... by Olaide N. Oyelade (14047002)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some medium-sized dimensional data... by Olaide N. Oyelade (14047002)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... by Olaide N. Oyelade (14047002)

Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

Symmetry test result. by Jiyong Moon (16819302)

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures by Hongpeng He (348094)

“…Both in silico design and data analysis descriptors and norm index were employed to encode the structural characteristics of binary IL mixtures. The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

“…<b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”

Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX by Umesh C. Sharma (10785063)

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity by George S. Watts (7962206)

Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports by Olivier Q. Groot (9370461)

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... by Ramsés Noguez Imm (6658637)

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen (12193358)

“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”

Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx by Ali Nabavi (21097424)

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”