Drug Resistance

Drug resistance, the ability of pathogens or cancer cells to withstand treatment, is a critical challenge in healthcare, demanding improved prediction and intervention strategies. Current research focuses on developing machine learning models, including recurrent neural networks (like GRUs) and ensemble methods (like ExtraTrees), often incorporating advanced feature extraction techniques from diverse data sources (e.g., single-cell genomics, patient health records represented as graphs) to predict drug resistance and identify contributing factors. These efforts aim to improve the accuracy and interpretability of resistance prediction, enabling earlier detection of at-risk individuals and facilitating personalized treatment approaches, ultimately enhancing patient outcomes and informing drug development.