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Titel:

Prediction of Complications and Surgery Duration in Primary Total Hip Arthroplasty Using Machine Learning: The Necessity of Modified Algorithms and Specific Data.

Dokumenttyp:
Journal Article
Autor(en):
Lazic, Igor; Hinterwimmer, Florian; Langer, Severin; Pohlig, Florian; Suren, Christian; Seidl, Fritz; Rückert, Daniel; Burgkart, Rainer; von Eisenhart-Rothe, Rüdiger
Abstract:
BACKGROUND: Machine Learning (ML) in arthroplasty is becoming more popular, as it is perfectly suited for prediction models. However, results have been heterogeneous so far. We hypothesize that an accurate ML model for outcome prediction in THA must be able to compute arthroplasty-specific data. In this study, we evaluate a ML approach applying data from two German arthroplasty-specific registries to predict adverse outcomes after THA, after careful evaluations of ML algorithms, outcome and inpu...     »
Zeitschriftentitel:
J Clin Med
Jahr:
2022
Band / Volume:
11
Heft / Issue:
8
Volltext / DOI:
doi:10.3390/jcm11082147
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/35456239
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert); Klinik und Poliklinik für Orthopädie und Sportorthopädie (Prof. von Eisenhart-Rothe); Klinik und Poliklinik für Unfallchirurgie (Prof. Biberthaler)
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