Flow diagram detailing the number of radiographs by data source and abnormality status from before exclusion for age (All Ages), after exclusion for age under 15 years, and after e... by Scott H. Lee (7430396)

Motif Code Unification and TDCM Supplemental by William Terry (22279591)

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ThermoPred: AI-Enhanced Quantum Chemistry Data Set and ML Toolkit for Thermochemical Properties of API-Like Compounds and Their Degradants by Diullio P. Santos (22770713)

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Reaction Alignment of the Tricarboxylic Acid (TCA) Cycle Network. by Adel Heydarabadipour (22290905)

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by Adel Heydarabadipour (22290905)

Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool by Pavel Izosimov (20096259)

“…</li><li><b>Cross-Platform Compatibility</b>: Designed with cross-platform functionality in mind, the script works seamlessly on Windows, macOS, Linux, Unix, and other operating systems where Python 3.6 or higher is installed.</li><li><b>Modular Design</b>: The script can be used as a standalone tool or imported as a module into other Python projects, enabling developers to easily integrate hardware identification into their applications.…”

Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research by Temitope Omogbene (18615415)

“…</li><li><b>Dataset 1D (highlighted_full_data_with_predictions.xlsx):</b> The complete harmonised dataset automatically classified using the trained XGBoost model.…”

A model of neural population dynamics for flexible sensorimotor control by Hari Kalidindi (17123467)

Modeling flowchart. by Jingru Dong (14076094)

“…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …”

Table 1_Machine learning models for mortality prediction in patients with spontaneous subarachnoid hemorrhage following ICU treatment.docx by Wenwen Hu (403536)

“…</p>Conclusions<p>In our study, the LR model exhibited superior discrimination in predicting risk of mortality among patients with spontaneous SAH compared to other models. …”

Image 1_Machine learning models for mortality prediction in patients with spontaneous subarachnoid hemorrhage following ICU treatment.jpeg by Wenwen Hu (403536)

“…</p>Conclusions<p>In our study, the LR model exhibited superior discrimination in predicting risk of mortality among patients with spontaneous SAH compared to other models. …”

Evaluation Metrics for LSTM Model and GRU Model. by Majed Alzara (20700224)

“…This study creates a predictive model just for Egypt’s construction industry that aims to predict a localized CCI to improve financial planning and lower risk. …”

Pythonproject-HCC by Roy Zhao (22503761)

Probabilities of normal and various cyber attack types over time sequence. by Mohanad Faeq Ali (21354273)

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Graphical abstract of HCAP. by Mohanad Faeq Ali (21354273)

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Recall analysis. by Mohanad Faeq Ali (21354273)

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FPR and FNR analysis based on varying cyber attack types. by Mohanad Faeq Ali (21354273)

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Analysis of IoMT data sources. by Mohanad Faeq Ali (21354273)

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<b> </b> Precision analysis. by Mohanad Faeq Ali (21354273)

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