Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx حسب Lian Li (49049)

"…Finally, an online predictive tool based on the optimal model was developed to provide real-time individualized VTE risk predictions for PMN patients.…"

Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf حسب Maliheh Aramon (6557906)

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

"…</p><h2>Model Architecture</h2><p dir="ltr">The model is based on <code>pysentimiento/robertuito-base-uncased</code> with the following modifications:</p><ul><li>A dense classification layer was added over the base model</li><li>Uses input IDs and attention masks as inputs</li><li>Generates a multi-class classification with 5 hate categories</li></ul><h2>Dataset</h2><p dir="ltr"><b>HATEMEDIA Dataset</b>: Custom hate speech dataset with categorization by type:</p><ul><li><b>Labels</b>: 5 hate type categories (0-4)</li><li><b>Preprocessing</b>:</li><li>Null values ​​removed from text and labels</li><li>Reindexing and relabeling (original labels are adjusted by subtracting 1)</li><li>Exclusion of category 2 during training</li><li>Conversion of category 5 to category 2</li></ul><h2>Training Process</h2><h3>Configuration</h3><ul><li><b>Batch size</b>: 128</li><li><b>Epoches</b>: 5</li><li><b>Learning rate</b>: 2e-5 with 10% warmup steps</li><li><b>Early stopping</b> with patience=2</li><li><b>Class weights</b>: Balanced to handle class imbalance</li></ul><h3>Custom Metrics</h3><ul><li>Recall for specific classes (focus on class 2)</li><li>Precision for specific classes (focus on class 3)</li><li>F1-score (weighted)</li><li>AUC-PR</li><li>Recall at precision=0.6 (class 3)</li><li>Precision at recall=0.6 (class 2)</li></ul><h2>Evaluation Metrics</h2><p dir="ltr">The model is evaluated using:</p><ul><li>Macro recall, precision, and F1-score</li><li>One-vs-Rest AUC</li><li>Accuracy</li><li>Per-class metrics</li><li>Confusion matrix</li><li>Full classification report</li></ul><h2>Technical Features</h2><h3>Data Preprocessing</h3><ul><li><b>Tokenization</b>: Maximum length of 128 tokens (truncation and padding)</li><li><b>Encoding of labels</b>: One-hot encoding for multi-class classification</li><li><b>Data split</b>: 80% training, 10% validation, 10% testing</li></ul><h3>Optimization</h3><ul><li><b>Optimizer</b>: Adam with linear warmup scheduling</li><li><b>Loss function</b>: Categorical Crossentropy (from_logits=True)</li><li><b>Imbalance handling</b>: Class weights computed automatically</li></ul><h2>Requirements</h2><p dir="ltr">The following Python packages are required:</p><ul><li>TensorFlow</li><li>Transformers</li><li>scikit-learn</li><li>pandas</li><li>datasets</li><li>matplotlib</li><li>seaborn</li><li>numpy</li></ul><h2>Usage</h2><ol><li><b>Data format</b>:</li></ol><ul><li>CSV file or Pandas DataFrame</li><li>Required column name: <code>text</code> (string type)</li><li>Required column name: Data type label (integer type, 0-4) - optional for evaluation</li></ul><ol><li><b>Text preprocessing</b>:</li></ol><ul><li>Automatic tokenization with a maximum length of 128 tokens</li><li>Long texts will be automatically truncated</li><li>Handling of special characters, URLs, and emojis included</li></ul><ol><li><b>Label encoding</b>:</li></ol><ul><li>The model classifies hate speech into 5 categories (0-4)</li><li><code>0</code>: Political hatred: Expressions directed against individuals or groups based on political orientation.…"

Optimal Time Intervals of Breech Births Dataset حسب Emma Spillane (11249121)

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

Table_1_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.XLSX حسب Qin-Yu Zhao (10014626)

Table_2_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.DOCX حسب Qin-Yu Zhao (10014626)

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

Datasets used for the study and their sources. حسب Peter N-jonaam Mahama (15347793)

"…<div><p>Introduction</p><p>Ghana is the first country in sub-Saharan Africa (SSA) to aim for universal health coverage (UHC). Based on Ghana’s UHC system, the accessibility and distribution of healthcare facilities were evaluated for 2020. …"

ACSA flowchart. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

ACSA pseudo code for proposed control process. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

Original waveform of fault 14. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

Original waveform of fault 15. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

ACSA convergence profile. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

ACSA plots for FAR vs FDR. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

SQP fitness progress for TEP [56]. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

Process fault of Tennessee Eastman process. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

ACSA fitness progress for TEP. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

Schematic diagram of TEP. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"

Detection of fault 15. حسب Faizan e Mustafa (18004325)

"…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …"