Titlebook: Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for; 10th Workshop, CLIP Cristina Oyarzun

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BIAS

Euphonious

The Scandinavian Countries and Finland,ny infected patients and deaths. CT image-based diagnosis of COVID-19 can provide quick and accurate diagnosis results. An automated segmentation method of infection regions in the lung provides a quantitative criterion for diagnosis. Previous methods employ whole 2D image or 3D volume-based process

cajole

Rural migrants in urban settingf labels represented in their data. For example, one client might have patient data with “healthy” pancreases only while datasets from other clients may contain cases with pancreatic tumors. The vanilla federated averaging algorithm makes it possible to obtain more generalizable deep learning-based

JUST

https://doi.org/10.1007/978-94-011-9416-7earch focused on the analysis of existing solutions for Federated Learning in the context of medical image classification. Selected frameworks: TensorFlow Federated, PySyft and Flower were tested and their usability was assessed. Additionally, experiments on classification of X-ray lung images with

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convulsion

Springer Series on Environmental Managementphy (CT) and ultrasound (US) of the thorax, playing an important role in the diagnosis and management of patients with coronavirus infection. The AI community reacted rapidly to the threat of the coronavirus pandemic by contributing numerous initiatives of developing AI technologies for interpreting

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