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Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning

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Published in:Journal of Cloud Computing : Advances, Systems and Applications
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Cloud Computing : Advances, Systems and Applications
description
discipline_display Internet
discipline_facet Internet
format Online Article
RSS Article
genre Journal Article
id rss_article:67225
institution FRELIP
journal_source_facet Journal of Cloud Computing : Advances, Systems and Applications
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
Internet
General
Internet
sub_discipline_display General
sub_discipline_facet General
subject_display Internet
General
Internet
Internet
General
Internet
subject_facet Internet
General
Internet
title Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_auth Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_full Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_fullStr Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_full_unstemmed Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_short Cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via LLM–VLM reasoning
title_sort cloud-edge collaborative interpretable fault classification for helical tomotherapy systems via llm–vlm reasoning
topic Internet
General
Internet
url https://link.springer.com/article/10.1186/s13677-026-00921-6