All the Places I Have Lived v3.0 by Christian Berg (18034411)

“…The work asks how identity shifts over time, and how technologies - especially those powered by algorithms—might influence the way we remember or even rewrite parts of ourselves. …”

Generating synthetic replicates of complex high-dimensional biological cell clusters by Mason Bradley (19850544)

“…The project uses synthetic cluster-generating benchmarking software often employed to assess clustering algorithms’ performances. However, through meticulous configuration via a cluster-based evaluation protocol, the generator is optimised to create high-dimensional synthetic CD34+ stem cell haematological models. …”

Supporting Data for "Intelligent prediction of steel corrosion in cementitious materials via machine learning" by Haodong Ji (11129136)

“…</li><li><b>Chapter </b><b>7</b> provides code related to symbolic learning for interpretable corrosion modeling, based on the data compiled from previous chapters.…”

Table 2_Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target.xls by Hao Wu (65943)

“…The top 40 bacterial species were utilized to develop ML models, with XGBoost demonstrating the highest predictive accuracy. …”

Table 1_Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target.xls by Hao Wu (65943)

“…The top 40 bacterial species were utilized to develop ML models, with XGBoost demonstrating the highest predictive accuracy. …”

Table 1_De novo KCNK4 variant caused epilepsy with febrile seizures plus, neurodevelopmental abnormalities, and hypertrichosis.xlsx by Hong-Jun Yan (15414734)

“…The identified variant was absent in normal populations, indicated to alter hydrogen bonds with surrounding residues by various protein modeling, predicted to be damaging for protein function by twenty algorithms, located in residues of high conservation across species, and classified as pathogenic by the ACMG guidelines. …”

Preprocessed GEFCom 2012 Wind Power Forecasting Dataset by Yuan Shi (22779782)

“…</p><p dir="ltr">This processed dataset is suitable for research and development in wind power forecasting models, offering a clean and standardized input for machine learning algorithms.…”

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li (4869760)

“…The models’ performance was evaluated for two-year prediction <i>via</i> concordance index and cumulative time-dependent ROC. …”

Supplementary file 1_Integrating bioinformatics and molecular experiments to reveal the critical role of the cellular energy metabolism-related marker PLA2G1B in COPD epithelial ce... by Jun Shi (289433)

“…</p>Material and methods<p>This research identified cell energy metabolism-related differentially expressed genes (CEM-DEGs) by collecting CEM-associated signatures from multiple public databases and integrating these markers with data from the GEO database. Subsequently, five machine learning algorithms—Boruta, Xgboost, GBM, SVM-RFE, and LASSO—were employed to screen for key variables. …”

Table 1_Integrating bioinformatics and molecular experiments to reveal the critical role of the cellular energy metabolism-related marker PLA2G1B in COPD epithelial cells.xlsx by Jun Shi (289433)

“…</p>Material and methods<p>This research identified cell energy metabolism-related differentially expressed genes (CEM-DEGs) by collecting CEM-associated signatures from multiple public databases and integrating these markers with data from the GEO database. Subsequently, five machine learning algorithms—Boruta, Xgboost, GBM, SVM-RFE, and LASSO—were employed to screen for key variables. …”

AI in Education by Shynggys Toktas (22633589)

“…In addition, it highlights potential risks and ethical challenges, including data privacy concerns, algorithmic bias, and the impact of generative AI tools on academic integrity.…”

Table1_Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.xlsx by Shengzhou Zheng (19729213)

“…Using 101 machine learning algorithms, the 10 most prognostic genes were selected. …”

DataSheet1_Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.docx by Shengzhou Zheng (19729213)

“…Using 101 machine learning algorithms, the 10 most prognostic genes were selected. …”

<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition by Qilin Li (535447)

“…It can accurately reflect the emotional changes of the human body by applying graphical-based algorithms or models. EEG signals are nonlinear signals. …”

Detection of Polycystic Ovarian Disease Using Probabilistic Optimum Deep Learning Feature Fusion by S. Jothimani (22173866)

“…Reformed differential evaluation (RDE) and reformed grey wolf (RGW) are two enhanced optimisation algorithms used to choose the best features; A unique probability-based serial strategy is employed to combine the best-selected attributes and categorised using deep learning techniques. …”

Cringe - Emotional manipulation as a tool of political control in Albanian digital campaigns (2025) by Edlira Gugu (21793610)

“…All personal data processed in compliance with EU GDPR regulations.…”

Image 1_Immune-molecular nexus in reproductive disorders: mechanisms linking POI and RSA.pdf by Chen Chen (6544)

“…</p>Objective<p>This study aims to identify new central genes and potential therapeutic drugs for RSA and POI by integrating multi transcriptome data and machine learning algorithms.</p>Methods<p>This study utilized RNA sequencing data from patients with POI and RSA to identify key hub genes associated with these diseases. …”

DATASET AI by Elena Stamate (18836305)

“…Performance metrics include accuracy, precision, recall, F1-score, and Matthews Correlation Coefficient (MCC).</p><p dir="ltr">All data have been de-identified and processed in accordance with institutional ethical standards.…”

Table 1_Supervised machine learning approaches for early detection of metabolic and udder health disorders in dairy cows using sensor-derived data.docx by Akvilė Girdauskaitė (22645433)

“…<p>This study assessed five supervised machine learning (ML) models. Automated devices that continuously captured milk composition and behavioral data were used to monitor 206 Holstein cows from two commercial dairy farms. …”

Table 2_Supervised machine learning approaches for early detection of metabolic and udder health disorders in dairy cows using sensor-derived data.docx by Akvilė Girdauskaitė (22645433)

“…<p>This study assessed five supervised machine learning (ML) models. Automated devices that continuously captured milk composition and behavioral data were used to monitor 206 Holstein cows from two commercial dairy farms. …”