Morphological Variation

Morphological variation, the study of differences in form and structure across individuals or species, is a crucial area of research aiming to understand how these variations arise, are maintained, and impact biological function and evolution. Current research utilizes machine learning, particularly deep learning models and gradient-boosted methods, to analyze morphological data from diverse sources, including images (e.g., histology, radio astronomy), text descriptions, and point clouds. These analyses are improving diagnostic accuracy in medicine (e.g., lymphoma subtyping, bone age assessment), enabling efficient data extraction from unstructured sources, and providing insights into evolutionary processes and the development of robust artificial systems.