Managing the intricacies of data sharing presents a big difficulty in the field of medical image analysis. This challenge has been addressed by the emergence of Swarm Learning (SL), a decentralized training strategy for deep learning models. Key data sources for bio-image analysis include surgical video analysis, histopathology, radiology, and single-cell analysis. We examine SL's effectiveness in handling these various data streams in this presentation. Our assessments included the use of MRI in radiology to detect breast cancer tumors and the prediction of cancer biomarkers in histology.
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