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Prediction of remaining surgery duration based on machine learning methods and laparoscopic annotation data.

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Title: Prediction of remaining surgery duration based on machine learning methods and laparoscopic annotation data.
Authors: Kostopoulos, Spiros1 (AUTHOR) skostopoulos@uniwa.gr, Cavouras, Dionisis1 (AUTHOR), Glotsos, Dimitris1 (AUTHOR), Loukas, Constantinos2 (AUTHOR)
Source: Biomedical Engineering / Biomedizinische Technik. Jun2025, Vol. 70 Issue 3, p229-239. 11p.
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 185650240
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Prediction of remaining surgery duration based on machine learning methods and laparoscopic annotation data.
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  Data: <searchLink fieldCode="JN" term="%22Biomedical+Engineering+%2F+Biomedizinische+Technik%22">Biomedical Engineering / Biomedizinische Technik</searchLink>. Jun2025, Vol. 70 Issue 3, p229-239. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=185650240
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1515/bmt-2024-0431
    Languages:
      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 229
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      – TitleFull: Prediction of remaining surgery duration based on machine learning methods and laparoscopic annotation data.
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            NameFull: Kostopoulos, Spiros
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            NameFull: Cavouras, Dionisis
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            NameFull: Glotsos, Dimitris
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            NameFull: Loukas, Constantinos
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            – D: 01
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              Text: Jun2025
              Type: published
              Y: 2025
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              Value: 70
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