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Cancer Prediction With Machine Learning of Thrombi From Thrombectomy in Stroke: Multicenter Development and Validation.

Joon Nyung HeoHyung Woo LeeYoung SeogSungeun KimJang Hyun BaekHyung Jong ParkKwon-Duk SeoGyu Sik KimHan-Jin ChoMinyoul BaikJoonsang YooJinkwon KimJun LeeYoon-Kyung ChangTae-Jin SongJung Hwa SeoSeong Hwan AhnHeow Won LeeIl KwonEunjeong ParkByung Moon KimDong Joon KimYoung Dae KimHyo Suk Nam
Published in: Stroke (2023)
Machine learning models may be used for prediction of cancer as the underlying cause or detection of occult cancer, using platelet-stained immunohistochemical slide images of thrombi obtained during endovascular thrombectomy.
Keyphrases
  • machine learning
  • papillary thyroid
  • squamous cell
  • atrial fibrillation
  • acute ischemic stroke
  • lymph node metastasis
  • big data
  • young adults
  • optical coherence tomography
  • sensitive detection