Optimizing Gene Expression Classification Models: Advanced Data Preparation and Evaluation Strategies for High-Feature Datasets

This project delves into optimizing classification models for high-dimensional, imbalanced gene expression datasets. It focuses on critical data preparation techniques and model evaluation strategies, emphasizing ROC AUC and Macro F1 metrics to enhance prediction accuracy and robustness.

Impact of Physical Activity Timing on Health Outcomes in Esophageal Cancer Patients

This is a research project that analyzes the impact of the circadian rhythm in the form of exercise oncology. Specifically, it combines data on physical activity (such as exercise, daily chores, walking etc.) with health data of patients to determine this.

ARIMA Stock Prediction

This R script is designed to utilize ARIMA (AutoRegressive Integrated Moving Average) models for predicting stock price movements based on historical data. The script employs various R packages to handle data manipulation, visualization, and ARIMA modeling effectively.