Rare Disease Atlas (Notre Dame summer research)

Big-Data ML project — Hate Speech & Topic Structure of r/MensRights (KU Leuven, "Collecting & Analyzing Big Data", Jan 2026, group of 4) Graduate-level supervised ML + NLP pipeline in R (quanteda, quanteda.textmodels, topicmodels, mallet, LDAvis, caret, glmnet, pROC). Full workflow: EDA & preprocessing, tokenization, collocations, word frequencies; manual annotation with inter-coder reliability; trained & compared Naive Bayes, Logistic Regression, Random Forest with hyperparameter tuning & cross-validation; evaluation via confusion matrix, precision/recall, F1, ROC/AUC; error analysis of false positives/negatives; applied best model to detect hate speech across the corpus. Topic modelling: LDA with coherence & exclusivity selection, topic interpretation, and topic frequency over time; TF-IDF. Includes a transparent "GenAI use" statement. Relevance: rigorous, reproducible supervised-ML + text-mining at master's level, incl. the annotation/reliability step that empirical text studies require.

R-based cleaning and analysis of the Google Play Store Apps dataset, with category-level insights for an ad-supported app business. Interactive Shiny dashboard linked separately.

Producto 1 del Portafolio Socioformativo de la asignatura Métodos de Investigación en Salud (MIN 26), Escuela de Medicina (UJMD). Presenta un mapa conceptual analítico-jerárquico elaborado en RMarkdown (DiagrammeR) que justifica el abordaje multiparadigmático —articulando el Positivismo (cuantitativo) y el Constructivismo (cualitativo)— frente al descontrol glucémico en Diabetes Mellitus Tipo 2 en El Salvador, integrando la evidencia científica con el humanismo clínico.