Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review
Background and purpose — Advancements in software and hardware have enabled the rise of clinical prediction models based on machine learning (ML) in orthopedic surgery. Given their growing popularity and their likely implementation in clinical practice we evaluated which outcomes these new models ha...
Main Authors: | Paul T Ogink, Olivier Q Groot, Aditya V Karhade, Michiel E R Bongers, F Cumhur Oner, Jorrit-Jan Verlaan, Joseph H Schwab |
---|---|
Format: | Article |
Language: | English |
Published: |
Medical Journals Sweden
2021-10-01
|
Series: | Acta Orthopaedica |
Online Access: | http://dx.doi.org/10.1080/17453674.2021.1932928 |
Similar Items
-
Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review
by: Olivier Q Groot, et al.
Published: (2021-07-01) -
Postoperative adverse events secondary to iatrogenic vascular injury during anterior lumbar spinal surgery
by: Olivier Groot, et al.
Published: (2021-01-01) -
Surgical treatment of traumatic fractures of the thoracic and lumbar spine: A systematic review
by: Timon F.G. Vercoulen, et al.
Published: (2024-01-01) -
The Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA) for predicting prolonged postoperative opioid prescription after total knee arthroplasty: an international validation study using 3,495 patients from a Taiwanese cohort
by: Cheng-Chen Tsai, et al.
Published: (2023-07-01) -
Role of surgical drains in orthopedics
by: Aditya Goel, et al.
Published: (2023-01-01)