AIMC Topic: Arthroplasty, Replacement, Hip

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Status of robot-assisted artificial total joint arthroplasty in China: a cross-sectional survey of joint surgeons.

International orthopaedics Nov 24, 2022
PURPOSE: The purpose of this study is to report on the use of Robotic-assisted total joint arthroplasty (RA-TJA) in China as well as the experience and expectations of Chinese doctors regarding this technology.
Humans Cross-Sectional Studies Arthroplasty, Replacement, Hip Arthroplasty, Replacement Orthopedic Surgeons Surveys and Questionnaires Robotics
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Deep Learning Dramatically Reduces the Work Associated with Image Cataloguing and Analysis: Commentary on an article by Pouria Rouzrokh, MD, MPH, MHPE, et al.: "Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry. A Stepwise Approach".

The Journal of bone and joint surgery. American volume Sep 21, 2022
Arthroplasty, Replacement, Hip Humans Deep Learning Radiography Registries
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Is Robotic-Assisted Technology Still Accurate in Total Hip Arthroplasty for Fibrous-Fused Hips?

The Journal of arthroplasty Aug 5, 2022
BACKGROUND: Total hip arthroplasty (THA) for fibrous-fused hips is technically demanding. This study aimed to evaluate the precision and accuracy, as well as the rate of conversion of robotic-assisted THA in such difficult patients.
Robotic Surgical Procedures Arthroplasty, Replacement, Hip Hip Prosthesis Acetabulum Robotics Humans Retrospective Studies
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Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry: A Stepwise Approach.

The Journal of bone and joint surgery. American volume Jul 21, 2022
BACKGROUND: Establishing imaging registries for large patient cohorts is challenging because manual labeling is tedious and relying solely on DICOM (digital imaging and communications in medicine) metadata can result in errors. We endeavored to estab...
Retrospective Studies Deep Learning Humans Registries Arthroplasty, Replacement, Hip Hip Prosthesis Acetabulum Radiography
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Deep Learning-Based Postoperative Recovery and Nursing of Total Hip Arthroplasty.

Computational and mathematical methods in medicine May 26, 2022
OBJECTIVE: To develop a deep learning-assisted recovery and nursing system after total hip arthroplasty and to conduct clinical trials in order to verify its accuracy.
Treatment Outcome Quality of Life Pain Deep Learning Arthroplasty, Replacement, Hip Humans Postoperative Complications
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Detecting total hip arthroplasty dislocations using deep learning: clinical and Internet validation.

Emergency radiology May 24, 2022
OBJECTIVE: Periprosthetic dislocations of total hip arthroplasty (THA) are time-sensitive injuries, as the longer diagnosis and treatment are delayed, the more difficult they are to reduce. Automated triage of radiographs with dislocations could help...
Joint Dislocations Neural Networks, Computer Retrospective Studies Internet Arthroplasty, Replacement, Hip Deep Learning Humans
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Automatic prosthetic-parameter estimation from anteroposterior pelvic radiographs after total hip arthroplasty using deep learning-based keypoint detection.

The international journal of medical robotics + computer assisted surgery : MRCAS Apr 4, 2022
BACKGROUND: X-ray is a necessary tool for post-total hip arthroplasty (THA) check-ups; however, parameter measurements are time-consuming. We proposed a deep learning tool, BKNet that automates localization of landmarks with parameter measurements.
Arthroplasty, Replacement, Hip Radiography Observer Variation Tomography, X-Ray Computed Deep Learning Humans
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John Charnley Award: Deep Learning Prediction of Hip Joint Center on Standard Pelvis Radiographs.

The Journal of arthroplasty Mar 16, 2022
BACKGROUND: Accurate hip joint center (HJC) determination is critical for preoperative planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and commonly used classification systems in primary and revision hip replacemen...
Deep Learning Pelvis Humans Biomechanical Phenomena Female Male Awards and Prizes Hip Joint Arthroplasty, Replacement, Hip
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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 Mar 15, 2022
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...
Male Middle Aged Hip Joint Arthroplasty, Replacement, Hip Pelvis Humans Aged Neural Networks, Computer Aged, 80 and over Tomography, X-Ray Computed Female Preoperative Period
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Artificial Intelligence for Automated Implant Identification in Total Hip Arthroplasty: A Multicenter External Validation Study Exceeding Two Million Plain Radiographs.

The Journal of arthroplasty Mar 7, 2022
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...
Reoperation Arthroplasty, Replacement, Hip Artificial Intelligence Humans Retrospective Studies ROC Curve
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