Diverse Population

Research on diverse populations focuses on mitigating biases in algorithms and models that arise from skewed data representation, impacting various fields from healthcare to AI. Current efforts utilize techniques like diffusion models for data augmentation, convolutional neural networks for image analysis, and deep learning frameworks to disentangle ancestry from phenotypic data for improved risk prediction across diverse groups. This work is crucial for ensuring fairness, accuracy, and generalizability of AI systems and predictive models, ultimately leading to more equitable and effective applications across different communities.