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Meta-lasso: new insight on infection prediction after minimally invasive surgery.

Cheng, Y ; Tang, Q ; et al.
In: Medical & biological engineering & computing, Jg. 62 (2024-06-01), Heft 6, S. 1703-1715
Online academicJournal

Titel:
Meta-lasso: new insight on infection prediction after minimally invasive surgery.
Autor/in / Beteiligte Person: Cheng, Y ; Tang, Q ; Li, X ; Ma, L ; Yuan, J ; Hou, X
Link:
Zeitschrift: Medical & biological engineering & computing, Jg. 62 (2024-06-01), Heft 6, S. 1703-1715
Veröffentlichung: New York, NY : Springer ; <i>Original Publication</i>: Stevenage, Eng., Peregrinus., 2024
Medientyp: academicJournal
ISSN: 1741-0444 (electronic)
DOI: 10.1007/s11517-024-03027-w
Schlagwort:
  • Humans
  • Male
  • Female
  • Middle Aged
  • Retrospective Studies
  • Aged
  • Algorithms
  • Minimally Invasive Surgical Procedures adverse effects
  • Lung Neoplasms surgery
  • Surgical Wound Infection etiology
  • Surgical Wound Infection diagnosis
  • Machine Learning
Sonstiges:
  • Nachgewiesen in: MEDLINE
  • Sprachen: English
  • Publication Type: Journal Article
  • Language: English
  • [Med Biol Eng Comput] 2024 Jun; Vol. 62 (6), pp. 1703-1715. <i>Date of Electronic Publication: </i>2024 Feb 13.
  • MeSH Terms: Minimally Invasive Surgical Procedures* / adverse effects ; Lung Neoplasms* / surgery ; Surgical Wound Infection* / etiology ; Surgical Wound Infection* / diagnosis ; Machine Learning* ; Humans ; Male ; Female ; Middle Aged ; Retrospective Studies ; Aged ; Algorithms
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  • Grant Information: 2021-010 Xuhui District Artificial Intelligence Medical Hospital Local Cooperation Project of 2021
  • Contributed Indexing: Keywords: Infection prediction; Long-tail problem; Machine learning; Meta learning
  • Entry Date(s): Date Created: 20240212 Date Completed: 20240507 Latest Revision: 20240507
  • Update Code: 20240508

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