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AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer

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Published in:PLOS ONE
Format: Online Article RSS Article
Published: 2026
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container_title PLOS ONE
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discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
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institution FRELIP
journal_source_facet PLOS ONE
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
subject_facet Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
title AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_auth AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_full AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_fullStr AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_full_unstemmed AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_short AI-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
title_sort ai-based prediction of recurrence after carbon ion radiotherapy for early stage non-small cell lung cancer
topic Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0342481