Predictive Model Development to Identify Failed Healing in Patients after Non–Union Fracture Surgery

Titel:: Predictive Model Development to Identify Failed Healing in Patients after Non–Union Fracture Surgery
Dokumenttyp:: Konferenzbeitrag
Autor(en):: Donié, Cedric; Reumann, Marie K.; Hartung, Tony; Braun, Benedikt J.; Histing, Tina; Endo, Satoshi; Hirche, Sandra
Stichworte:: machine learning, predictive models, non-union, bone healing, fracture healing, failed healing, pseudoarthrosis, personalized medicine
Kongress- / Buchtitel:: Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2024)
Verlagsort:: Orlando, Florida, U.S.A.
Jahr:: 2024
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