AI Medical Compendium Journal:
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA

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A practical guide to the development and deployment of deep learning models for the orthopedic surgeon: part II.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Deep learning has the potential to be one of the most transformative technologies to impact orthopedic surgery. Substantial innovation in this area has occurred over the past 5 years, but clinically meaningful advancements remain limited by a disconn...

A practical guide to the development and deployment of deep learning models for the Orthopedic surgeon: part I.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Deep learning has a profound impact on daily life. As Orthopedics makes use of this rapid escalation in technology, Orthopedic surgeons will need to take leadership roles on deep learning projects. Moreover, surgeons must possess an understanding of ...

Unsupervised machine learning methods and emerging applications in healthcare.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Unsupervised machine learning methods are important analytical tools that can facilitate the analysis and interpretation of high-dimensional data. Unsupervised machine learning methods identify latent patterns and hidden structures in high-dimensiona...

Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: To (1) develop a deep-learning (DL) algorithm capable of producing limb-length and knee-alignment measurements, and (2) determine the association between limb-length discrepancy (LLD), coronal-plane alignment, osteoarthritis (OA) severity, a...

Supervised machine learning and associated algorithms: applications in orthopedic surgery.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Supervised learning is the most common form of machine learning utilized in medical research. It is used to predict outcomes of interest or classify positive and/or negative cases with a known ground truth. Supervised learning describes a spectrum of...

The development and deployment of machine learning models.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Applications of artificial intelligence, specifically machine learning, are becoming increasingly popular in Orthopaedic Surgery, and medicine as a whole. This growing interest is shared by data scientists and physicians alike. However, there is an a...

Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Evaluating lower extremity alignment using full-leg plain radiographs is an essential step in diagnosis and treatment of patients with knee osteoarthritis. The study objective was to present a deep learning-based anatomical landmark recognit...

Machine learning and conventional statistics: making sense of the differences.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
The application of machine learning (ML) to the field of orthopaedic surgery is rapidly increasing, but many surgeons remain unfamiliar with the nuances of this novel technique. With this editorial, we address a fundamental topic-the differences betw...