turkmath.org

The exponential growth of medical and biomedical data from laboratories and hospitals worldwide has placed a substantial burden on healthcare professionals, highlighting an urgent need for automated data analysis. With a shortage of experts to interpret this vast information, automation has become essential for applications such as analyzing DNA damage and repair at the cellular level, examining biomedical images in cancer immunology, accurately distinguishing inflammatory diseases, etc.

This talk explores how collaborative efforts between data-collecting specialists, mathematicians with expertise in functions and their properties, image-processing experts, and machine-learning researchers can drive the development of efficient, automated solutions. By combining expertise across these fields, we aim to address real-world healthcare challenges and streamline data interpretation, ultimately advancing biomedical research and easing the workload on healthcare professionals.