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Development and validation of machine learning tools for predicting postoperative complications in acute calculous cholecystitis

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Τίτλος: Development and validation of machine learning tools for predicting postoperative complications in acute calculous cholecystitis
Συγγραφείς: Cicerone, OttaviaAff1, Aff2, Frassini, SimoneAff1, Aff2, Gallotti, AnnaAff4, Vanoli, AlessandroAff3, Ansaloni, LucaAff1, Aff2, Maestri, MarcelloAff1, Aff2, IDs13304025024768_cor1, Fugazzola, PaolaAff2, S.P.Ri.M.A.C.C.Aff2, Collaborative GroupAff2
Πηγή: Updates in Surgery. :1-12
Βάση Δεδομένων: Springer Nature Journals
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  – Url: https://dx.doi.org/doi:10.1007/s13304-025-02476-8
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  Data: Development and validation of machine learning tools for predicting postoperative complications in acute calculous cholecystitis
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  Data: <i>Updates in Surgery</i>. :1-12
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        Value: 10.1007/s13304-025-02476-8
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      – TitleFull: Development and validation of machine learning tools for predicting postoperative complications in acute calculous cholecystitis
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              Type: published
              Y: 2025
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            – TitleFull: Updates in Surgery
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