AIMC Topic: Hip

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Deep learning based screening model for hip diseases on plain radiographs.

PloS one Feb 13, 2025
INTRODUCTION: The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs.
Hip Adult Male Middle Aged Radiography Algorithms Hip Joint Female Deep Learning Aged ROC Curve Humans
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Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.

Scientific reports Jan 2, 2025
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addre...
Female Aged Male Humans Tomography, X-Ray Computed Middle Aged Hip Deep Learning Uncertainty Image Processing, Computer-Assisted ROC Curve Muscle, Skeletal
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Artificial Intelligence Applications in MR Imaging of the Hip.

Magnetic resonance imaging clinics of North America Sep 26, 2024
Artificial intelligence (AI) can provide significant utility in the management of hip disorders by analyzing MR images. AI can automate image segmentation with success. Current models have been successfully tested in the diagnosis of osteoarthritis, ...
Hip Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Hip Joint Humans Artificial Intelligence
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Deep Learning for Automated Classification of Hip Hardware on Radiographs.

Journal of imaging informatics in medicine Sep 12, 2024
PURPOSE: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiographs, which can be clinically implemented to decrease radiologist workload and improve consistency among radiology reports.
Humans Neural Networks, Computer Deep Learning Radiography Hip Joint Arthroplasty, Replacement, Hip Retrospective Studies Female Male Hip Hip Prosthesis
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Experiment-free exoskeleton assistance via learning in simulation.

Nature Jun 12, 2024
Exoskeletons have enormous potential to improve human locomotive performance. However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws. Here we show an experiment-free meth...
Running Hip Exoskeleton Device Self-Help Devices Persons with Disabilities Robotics Walking Humans Computer Simulation Learning
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Gait training using a wearable robotic hip device for incomplete spinal cord injury: A preliminary study.

The journal of spinal cord medicine Nov 7, 2023
CONTEXT/OBJECTIVE: To explore changes in gait functions for patients with chronic spinal cord injury (SCI) before and after standard rehabilitation and rehabilitation with a wearable hip device, explore the utility of robot-assisted gait training (RA...
Wearable Electronic Devices Hip Robotics Adult Exercise Therapy Gait Disorders, Neurologic Gait Humans Male Female Spinal Cord Injuries Middle Aged
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Development and Validation of an Automated Classification System for Osteonecrosis of the Femoral Head Using Deep Learning Approach: A Multicenter Study.

The Journal of arthroplasty Aug 11, 2023
BACKGROUND: Accurate classification can facilitate the selection of appropriate interventions to delay the progression of osteonecrosis of the femoral head (ONFH). This study aimed to perform the classification of ONFH through a deep learning approac...
Humans Femur Head Hip Retrospective Studies Deep Learning Femur Head Necrosis
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Two-stage multi-task deep learning framework for simultaneous pelvic bone segmentation and landmark detection from CT images.

International journal of computer assisted radiology and surgery Jun 15, 2023
PURPOSE: Pelvic bone segmentation and landmark definition from computed tomography (CT) images are prerequisite steps for the preoperative planning of total hip arthroplasty. In clinical applications, the diseased pelvic anatomy usually degrades the ...
Pelvis Hip Deep Learning Image Processing, Computer-Assisted Humans Acetabulum Tomography, X-Ray Computed
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Machine Learning Algorithms Predict Clinically Significant Improvements in Satisfaction After Hip Arthroscopy.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association Dec 24, 2020
PURPOSE: To develop machine learning algorithms to predict failure to achieve clinically significant satisfaction after hip arthroscopy.
Adult Hip Male Case-Control Studies Algorithms Female Humans Young Adult Neural Networks, Computer Calibration Machine Learning ROC Curve Postoperative Period Arthroscopy Treatment Outcome Risk Patient Satisfaction
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Automated measurement of hip-knee-ankle angle on the unilateral lower limb X-rays using deep learning.

Physical and engineering sciences in medicine Nov 30, 2020
Significant inherent extra-articular varus angulation is associated with abnormal postoperative hip-knee-ankle (HKA) angle. At present, HKA is manually measured by orthopedic surgeons and it increases the doctors' workload. To automatically determine...
X-Rays Deep Learning Hip Lower Extremity Knee Ankle Humans Retrospective Studies Reproducibility of Results
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