Orthopedics

Latest AI and machine learning research in orthopedics for healthcare professionals.

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Reducing Metabolic Cost During Planetary Ambulation Using Robotic Actuation.

Current spacesuits are cumbersome and metabolically expensive. The use of robotic actuators could i...

Using machine learning to automate ultrasound-based classification of butt-fused joints in medium-density polyethylene gas pipes.

Polyethylene (PE) pipes are widely used in gas distribution. Their joints are prone to various flaws...

Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?

BACKGROUND: Vertebral fractures are the most common osteoporotic fractures in older individuals. Rec...

Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach.

The human diet consists of a complex mixture of components. To realistically assess dietary impacts ...

Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femo...

Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.

BACKGROUND: The referral process for consultation with a spine surgeon remains inefficient, given a ...

Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training.

As an important class of spiking neural networks (SNNs), recurrent spiking neural networks (RSNNs) p...

A Deep-Learning-Based, Fully Automated Program to Segment and Quantify Major Spinal Components on Axial Lumbar Spine Magnetic Resonance Images.

OBJECTIVE: The paraspinal muscles have been extensively studied on axial lumbar magnetic resonance i...

A Deep Learning System for Synthetic Knee Magnetic Resonance Imaging: Is Artificial Intelligence-Based Fat-Suppressed Imaging Feasible?

MATERIALS AND METHODS: This single-center study was approved by the institutional review board. Arti...

Comparison of Knowledge Databases to Be Used in Automated Monitoring of Orthopedic Medical Devices.

Surveillance and traceability of medical devices (MD) is a challenge in health care systems. In the ...

Rib fracture detection in computed tomography images using deep convolutional neural networks.

To evaluate the rib fracture detection performance in computed tomography (CT) images using a softwa...

FS-GBDT: identification multicancer-risk module via a feature selection algorithm by integrating Fisher score and GBDT.

Cancer is a highly heterogeneous disease caused by dysregulation in different cell types and tissues...

Robotic-Assisted Surgery Training (RAST) Program: An Educational Research Protocol.

Technology has had a dramatic impact on how diseases are diagnosed and treated. Although cut, sew, a...

Artificial Intelligence in Spine Care.

Artificial intelligence is an exciting and growing field in medicine to assist in the proper diagnos...

[Mirror-type rehabilitation training with dynamic adjustment and assistance for shoulder joint].

The real physical image of the affected limb, which is difficult to move in the traditional mirror t...

[A cadaveric experimental study on domestic robot-assisted total knee arthroplasty].

OBJECTIVE: To simulate and validate the performance, accuracy, and safety of the Yuanhua robotic-ass...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Although clinical and laboratory data have long been used to guide medical practice, this informatio...

[Effect of rehabilitation robot rehabilitation training synchronizing acupuncture exercise therapy on postoperative rehabilitation with hip fracture].

OBJECTIVE: To compare the therapeutic effect between rehabilitation robot rehabilitation training sy...

Strategies to Improve Convolutional Neural Network Generalizability and Reference Standards for Glaucoma Detection From OCT Scans.

PURPOSE: To develop and evaluate methods to improve the generalizability of convolutional neural net...

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