Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Although the presented work was focused on 2-D binary channelized structures (geological facies), the applied principles are general and it can be extended to the characterization and recovery of other geological signals with spatial structure in under sampling contexts. …”

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

Bayesian sequential design for sensitivity experiments with hybrid responses by Yuxia Liu (1779592)

“…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”

Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports by Olivier Q. Groot (9370461)

“…The aim of this study was to develop a natural language processing (NLP) algorithm for binary classification (single metastasis versus two or more metastases) in bone scintigraphy reports of patients undergoing surgery for bone metastases.…”

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”

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

“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction by Raul A. Flores (2910539)

“…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…”

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx by Yuhong Huang (115702)

“…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …”

DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

“…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”

Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

“…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”

Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx by Yuan Liu (88411)

“…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”

DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx by Jun Zhang (48506)

“…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …”

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

“…</p>Results and Discussion<p>Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. …”

Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx by Ali Nabavi (21097424)

“…Demographic, clinical, and heavy metal biomarker data (e.g., blood lead and cadmium levels) were analyzed as features, with hearing loss status—defined as a pure-tone average threshold exceeding 25 dB HL across 500, 1,000, 2000, and 4,000 Hz in the better ear—serving as the binary outcome. Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach by Sanaa Badr (20628838)

“…Binary classification models were developed to classify cases into two groups: those transferring two or fewer embryos and those transferring three or four. …”

Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx by Yanbo Sun (2202439)

“…Five machine learning models were deployed for the binary classification task of DM, and their performance was evaluated using the area under the curve (AUC). …”