Craig Myles

Craig Myles serves as a Research Fellow in the School of Computer Science at the University of St Andrews, UK. His work focuses on applying advanced deep learning techniques to medical imaging challenges, particularly in cancer detection systems.

His research spans foundation models, self-supervised learning, and residual neural networks applied to oncology imaging. Key contributions include developing novel approaches for colorectal cancer biomarker detection in small datasets and optimizing mammography classification accuracies through divide-and-conquer methodologies. His fingerprint reveals strong specialization in Deep Learning Method, Classification Accuracy, and Foundation Model applications within medical computer vision.

Analysis of his recent publications shows a consistent trajectory toward solving data scarcity problems in medical AI through innovative architectural adaptations of foundation models. His work bridges computer science theory with critical clinical applications in cancer diagnostics.

Notable datasets he contributed to include SurGen (1020 H&E-stained Whole Slide Images) and Patch-level UNI feature embeddings for colorectal cancer analysis, demonstrating significant infrastructure contributions to the field.

He actively participates in major conferences including Medical Image Understanding and Analysis (MIUA 2024) and Scottish Informatics and Computer Science Alliance events, while also engaging in public outreach through Doors Open events at the School of Computer Science.