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Machine learning for predicting successful extubation in patients receiving mechanical ventilation.
Igarashi, Yutaka; Ogawa, Kei; Nishimura, Kan; Osawa, Shuichiro; Ohwada, Hayato; Yokobori, Shoji.
Affiliation
  • Igarashi Y; Department of Emergency and Critical Care Medicine, Nippon Medical School, Tokyo, Japan.
  • Ogawa K; Department of Industrial Administration, Tokyo University of Science, Chiba, Japan.
  • Nishimura K; Department of Industrial Administration, Tokyo University of Science, Chiba, Japan.
  • Osawa S; Department of Emergency and Critical Care Medicine, Nippon Medical School, Tokyo, Japan.
  • Ohwada H; Department of Industrial Administration, Tokyo University of Science, Chiba, Japan.
  • Yokobori S; Department of Emergency and Critical Care Medicine, Nippon Medical School, Tokyo, Japan.
Front Med (Lausanne) ; 9: 961252, 2022.
Article in En | MEDLINE | ID: mdl-36035403
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Med (Lausanne) Year: 2022 Document type: Article Affiliation country: Country of publication:
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Med (Lausanne) Year: 2022 Document type: Article Affiliation country: Country of publication: