The Assistance of Applied Mathematics in Biomedical Sciences

This paper focuses on the facilitating role of applied mathematics in biomedical sciences. As an interdisciplinary field integrating biology and medicine, biomedical science faces challenges such as handling large amounts of data and integrating multiple disciplines in its development. Mathematics, statistics, and computational methods have played a significant role in this field. This paper finds that the SIR model in mathematical modeling has been instrumental in epidemic prevention and control, the NCC model has provided new ideas for cancer treatment, and the QSAR model has played a crucial role in drug development. Statistical principles such as regression analysis and variance analysis are indispensable in biomedical research. Computational methods also have extensive and critical applications in bioinformatics, medical imaging, systems biology, and other areas. These disciplines are interdependent, transforming raw biological data into actionable insights. Although there are challenges such as data integration, their continuous integration and technological advancements are expected to open up new frontiers in areas such as precision medicine and drive the future development of human healthcare.