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Comment on "an interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study".

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Title: Comment on "an interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study".
Authors: Mayasala P; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India., Kumar GS; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India., Neelu L; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India. drlalband.neelu@mallareddyuniversity.ac.in.
Source: Journal of anesthesia, analgesia and critical care [J Anesth Analg Crit Care] 2026 Jun 30; Vol. 6 (1). Date of Electronic Publication: 2026 Jun 30.
Publication Type: Letter
Journal Info: Publisher: Springer Nature, BioMed Central Ltd Country of Publication: England NLM ID: 9918591885906676 Publication Model: Electronic Cited Medium: Internet ISSN: 2731-3786 (Electronic) Linking ISSN: 27313786 NLM ISO Abbreviation: J Anesth Analg Crit Care Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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DbLabel: MEDLINE Ultimate
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AccessLevel: 2
PubType: Editorial & Opinion
PubTypeId: editorialOpinion
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  Data: Comment on "an interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study".
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  Label: Authors
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  Data: <searchLink fieldCode="AU" term="%22Mayasala+P%22">Mayasala P</searchLink>; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India.<br /><searchLink fieldCode="AU" term="%22Kumar+GS%22">Kumar GS</searchLink>; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India.<br /><searchLink fieldCode="AU" term="%22Neelu+L%22">Neelu L</searchLink>; Department of Information Technology, Malla Reddy University, Hyderabad, Telangana, 500100, India. drlalband.neelu@mallareddyuniversity.ac.in.
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  Data: <searchLink fieldCode="JN" term="%229918591885906676%22">Journal of anesthesia, analgesia and critical care</searchLink> [J Anesth Analg Crit Care] 2026 Jun 30; Vol. 6 (1). <i>Date of Electronic Publication: </i>2026 Jun 30.
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  Data: Letter
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+Nature%2C+BioMed+Central+Ltd%22">Springer Nature, BioMed Central Ltd </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>9918591885906676 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2731-3786 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2227313786%22">27313786 </searchLink><i>NLM ISO Abbreviation: </i>J Anesth Analg Crit Care <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42380954
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1186/s44158-026-00380-0
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      – Code: eng
        Text: English
    Titles:
      – TitleFull: Comment on "an interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study".
        Type: main
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            NameFull: Mayasala P
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            NameFull: Kumar GS
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            NameFull: Neelu L
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          Dates:
            – D: 30
              M: 06
              Text: 2026 Jun 30
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 2731-3786
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              Value: 6
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              Value: 1
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            – TitleFull: Journal of anesthesia, analgesia and critical care
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