IoMT devices and attack overview in the CICIoMT2024 dataset. by Mohanad Faeq Ali (21354273)

Subjects:

Pseudocode for machine learning models. by Jingru Dong (14076094)

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

Data features examined for potential biases. by Harry Hochheiser (3413396)

“…<div><p><b>Objective:</b> To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score.…”

Analysis topics. by Harry Hochheiser (3413396)

“…<div><p><b>Objective:</b> To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score.…”

Code for the HIVE Appendicitis prediction modelRepository with LLM_data_extractor_optuna for automated feature extraction by Anoeska Schipper (18513465)

“…</p><p dir="ltr"><b>LLM Data Extractor optuna repo</b> is a Python framework for generating and evaluating clinical text predictions using large language models (LLMs) like <code>qwen2.5</code>. …”

Motif Code Theory Figshare Documentation by William Terry (22279591)

“…Simulations in Python/NetworkX (Figshare DOI: 10.6084/m9.figshare.30179545) ensure reproducibility. …”

Overview of the implemented simulation tool and training framework in Diffrax. by Paul van Lent (16876977)

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

“…However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. …”

Flowchart of the study participants. by Saeid Rasouli (20370998)

“…<div><p>Background</p><p>Optic neuritis (ON) can be an initial clinical presentation of multiple sclerosis This study aims to provide a practical predictive model for identifying at-risk ON patients in developing MS.…”

Feature importance of variables. by Saeid Rasouli (20370998)

“…<div><p>Background</p><p>Optic neuritis (ON) can be an initial clinical presentation of multiple sclerosis This study aims to provide a practical predictive model for identifying at-risk ON patients in developing MS.…”

FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair by Sakina Fatima (15362704)

“…<p dir="ltr">This is the replication package associated with the paper: 'FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test for Code Repair'</p><p><br></p><p dir="ltr">### Requirements</p><p dir="ltr">This is a list of all required python packages:</p><p dir="ltr">-imbalanced_learn==0.8.1</p><p dir="ltr">-numpy==1.19.5</p><p dir="ltr">-pandas==1.3.3</p><p dir="ltr">-transformers==4.10.2</p><p dir="ltr">-torch==1.5.0</p><p dir="ltr">-scikit_learn==0.24.2</p><p dir="ltr">-openai==v0.28.1</p><p><br></p><p dir="ltr">#Automated tool for labelling dataset with flaky test fix categories</p><p><br></p><p dir="ltr">This is a step-by-step guideline for automatically labelling dataset with flaky test fix categories</p><p><br></p><p><br></p><p dir="ltr">### Input Files:</p><p dir="ltr">This is a an input file that is required to accomplish this step:</p><p dir="ltr">* Data/IdoFT_dataset_filtered.csv</p><p dir="ltr">https://figshare.com/s/47f0fb6207ac3f9e2351</p><p><br></p><p dir="ltr">### Output Files:</p><p dir="ltr">* Results/IdoFT_dataset_filtered.csv</p><p><br></p><p><br></p><p dir="ltr">### Replicating the experiment</p><p><br></p><p dir="ltr">This experiment can be executed using the following commands after navigating to the `Code\` folder:</p><p><br></p><p dir="ltr">```console</p><p dir="ltr">bash Automated_labelling_tool.sh</p><p>```</p><p><br></p><p dir="ltr">It will generate the dataset required to run our prediction models to predict the category of the fix, given a flaky test code</p><p><br></p><p>---</p><p><br></p><p dir="ltr"># Prediction models for fix categories using the test case code</p><p><br></p><p dir="ltr">This is the guideline for replicating the experiments we used to evaluate our prediction models i.e. …”

Melbournevirus protein structure prediction - AlphaFold3 by Lars Mühlberg (21524075)

“…Number of multimer predictions per model was set to 1. The heteromultimeric model of MEL_149 and MEL_368 has been predicted with the AlphaFold3 online search server. pTM and ipTM scores were extracted from .json files using R and PAE data was extracted using python 3. …”

Data Sheet 1_Computation of domination degree-based topological indices using python and QSPR analysis of physicochemical and ADMET properties for heart disease drugs.pdf by Geethu Kuriachan (20865374)

“…QSPR models are developed to assess the ability of these indices to predict key properties, offering insights into their effectiveness for drug design.…”

A free tutorial book from NSF Cybertraining C2D: Cybertraining for Chemical Data scientists by Xiangliang Zhang (19460047)

“…In the following chapters, 4 through 9, we focus on specific chemical tasks, dedicating each chapter to solving a distinct problem using these machine learning techniques, including molecular property prediction, molecular optimization, reaction outcome prediction, retrosynthesis, yield prediction and Large Language Models (LLMs) for Chemistry. …”

Study workflow diagram. by Alemu Birara Zemariam (17540938)

“…The performance of the predictive model was evaluated using evaluation metrics value through Python software. …”

Stunting final dataset. by Alemu Birara Zemariam (17540938)

“…The performance of the predictive model was evaluated using evaluation metrics value through Python software. …”

A mean SHAP value report. by Alemu Birara Zemariam (17540938)

“…The performance of the predictive model was evaluated using evaluation metrics value through Python software. …”

A waterfall plot analysis. by Alemu Birara Zemariam (17540938)

“…The performance of the predictive model was evaluated using evaluation metrics value through Python software. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”