This project aims to improve the accuracy and robustness of disease prediction models using genomic data from the UK Biobank. We will leverage Polygenic Risk Scores (PRS) to assess individuals’ genetic predisposition to various diseases. By integrating our East Asian dataset with the UK Biobank dataset, we seek to address challenges such as overfitting and underfitting. We will evaluate the performance of PRS models using independent cohorts from the UK Biobank to ensure the reliability of disease prediction models. Additionally, the validation dataset from the UK Biobank will enable us to assess prediction accuracy across diverse populations. This approach will strengthen the robustness and generalizability of PRS-based disease prediction models. Sophisticated PRS models can play a significant role in early disease detection and diagnosis by identifying high-risk individuals before clinical symptoms emerge. Through the analysis of large-scale genomic and phenotypic data, we can personalize healthcare strategies and contribute to more precise prevention and treatment approaches. Ultimately, our study will support the advancement of patient-centered medical care and improve public health by refining genetic risk assessment and facilitating future clinical applications.
