AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Arthroplasty, Replacement, Hip

Showing 61 to 70 of 133 articles

Clear Filters

Utility of a novel integrated deep convolutional neural network for the segmentation of hip joint from computed tomography images in the preoperative planning of total hip arthroplasty.

Journal of orthopaedic surgery and research
PURPOSE: Preoperative three-dimensional planning is important for total hip arthroplasty. To simulate the placement of joint implants on computed tomography (CT), pelvis and femur must be segmented. Accurate and rapid segmentation of the hip joint is...

Artificial Intelligence for Automated Implant Identification in Total Hip Arthroplasty: A Multicenter External Validation Study Exceeding Two Million Plain Radiographs.

The Journal of arthroplasty
BACKGROUND: The surgical management of complications after total hip arthroplasty (THA) necessitates accurate identification of the femoral implant manufacturer and model. Automated image processing using deep learning has been previously developed a...

The Ability of Deep Learning Models to Identify Total Hip and Knee Arthroplasty Implant Design From Plain Radiographs.

The Journal of the American Academy of Orthopaedic Surgeons
INTRODUCTION: The surgical management of patients with failed total hip or knee arthroplasty (THA and TKA) necessitates the identification of the implant manufacturer and model. Failure to accurately identify implant design leads to delays in care, i...

Proof of concept study for using UR10 robot to help total hip replacement.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The demand for total hip replacement (THR) for treating osteoarthritis has grown substantially worldwide. The existing robotic systems used in THR are invasive and costly. This study aims to develop a less-invasive and low-cost robotic sy...

Automated detection and explainability of pathological gait patterns using a one-class support vector machine trained on inertial measurement unit based gait data.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Machine learning approaches for the classification of pathological gait based on kinematic data, e.g. derived from inertial sensors, are commonly used in terms of a multi-class classification problem. However, there is a lack of research ...

Robotics Versus Navigation Versus Conventional Total Hip Arthroplasty: Does the Use of Technology Yield Superior Outcomes?

The Journal of arthroplasty
BACKGROUND: The use of technology such as navigation and robotic systems may improve the accuracy of component positioning in total hip arthroplasty (THA), but its impact on patient-reported outcome measures (PROMs) remains unclear. This study aims t...

[The superiority of navigation and robotics in hip arthroplasty: fact or myth?].

Der Orthopade
Computer-assisted surgery represents a relatively novel treatment option in total hip arthroplasty, which has been supported by the technological progress over the latest decades. Navigation and robotics enable increasing the precision of cup positio...

Value of 3D preoperative planning for primary total hip arthroplasty based on artificial intelligence technology.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate preoperative planning is an important step for accurate reconstruction in total hip arthroplasty (THA). Presently, preoperative planning is completed using either a two-dimensional (2D) template or three-dimensional (3D) mimics s...

A Deep Learning Tool for Automated Radiographic Measurement of Acetabular Component Inclination and Version After Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: Inappropriate acetabular component angular position is believed to increase the risk of hip dislocation after total hip arthroplasty. However, manual measurement of these angles is time consuming and prone to interobserver variability. Th...