Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

The general processing diagram used to create OSSL. by José L. Safanelli (20552654)

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A typical BCI system depicting the flow and processing of EEG data. by Gursimran Singh (575288)

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Heart and Lung Sounds Dataset Recorded from a Clinical Manikin using Digital Stethoscope (HLS-CMDS) by Yasaman Torabi (21305930)

Subjects: “…Bioinformatic methods development…”

Stage 3 Workshops: Investigating the Learning Mechanics - Game Mechanics (LM-GM) model for the development of digital game-based learning by Glen Shearer (9834266)

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A Five-Step Workflow to Manually Annotate Unstructured Data into Training Dataset for Natural Language Processing by Yunshu Zhu (19583983)

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Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. by Miray Unlu Yazici (14792680)

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Data Sheet 1_Exploring immune-inflammation markers in psoriasis prediction using advanced machine learning algorithms.pdf by Li Yang (6520)

“…Subsequently, nine classification algorithms were developed using the processed training set, including random forest, neural networks, XGBoost, k-nearest neighbors, gradient boosting, logistic regression, naïve Bayes, AdaBoost, and SVMs. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

The Search process of the genetic algorithm. by Wenguang Li (6528113)

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Data Sheet 1_Person-based design and evaluation of MIA, a digital medical interview assistant for radiology.pdf by Kerstin Denecke (11534035)

Enhancing off-policy optimisation in structured Markov decision processes via Thompson Sampling by Sourav Ganguly (293262)

“…<p>Reinforcement Learning (RL) provides a framework for solving sequential decision-making tasks, yet limited and potentially unsafe data hinder its training process. …”

The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

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<b>Table </b><b>1</b><b>: Types of Sentiment</b><b> Classification</b><b>Table </b><b>2</b><b>: Types of Sentiment</b><b> </b><b>Analysis Techniques/Algorithms</b><b>Table 3: Liter... by Ritu SHARMA (15463307)

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Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to model the data. …”

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…<div><p>Background and objectives</p><p>Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

Stage 2 Interviews: Investigating models for the development of online educational interventions by Glen Shearer (9834266)

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Identifying factors affecting driver takeover time and crash risk during the automated driving takeover process by Changshuai Wang (20544152)