Explainable AI to unveil cellular autophagy dynamics.

ABSTRACT: Autophagy is a fundamental intracellular renovation process vital for maintaining cellular homeostasis through the degradation and recycling of damaged components. It is implicated in numerous pathological conditions, including cancer and neurodegenerative diseases. However, its dynamic nature and complexity pose challenges for manual analysis. In this study, we present a computational pipeline that leverages advanced deep learning models to automate the analysis of autophagic processes in 6,240 fluorescence microscopy images from the CELLULAR dataset. Our framework integrates object detection, cell segmentation, classification by autophagic state, cellular tracking, and explainability methods for interpretability. We achieved optimal results using YOLOv8 for object detection with a mAP50

SUBMITTER: Presacan O 

PROVIDER: S-EPMC12425229 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature