Disease Biomarkers

Disease biomarkers are measurable indicators used to diagnose, monitor, or predict disease progression, with current research heavily focused on identifying and validating these markers across various diseases. Advanced machine learning techniques, including generative adversarial networks (GANs) and XGBoost, are increasingly employed to analyze high-dimensional data from diverse sources like genomics, imaging (MRI, PET), and even voice recordings, improving biomarker discovery and predictive modeling. This work holds significant promise for improving early diagnosis, personalized treatment strategies, and ultimately, patient outcomes across a range of conditions, from cancer and Alzheimer's disease to heart failure and COVID-19. The integration of multimodal data and explainable AI frameworks is a key trend, enhancing both the accuracy and interpretability of biomarker-based predictions.