Orthopedics

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

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Deep learning-based identification of spine growth potential on EOS radiographs.

OBJECTIVES: To develop an automatic computer-based method that can help clinicians in assessing spin...

Artificial intelligence in osteoarthritis detection: A systematic review and meta-analysis.

OBJECTIVES: As an increasing number of studies apply artificial intelligence (AI) algorithms in oste...

Deep-learning segmentation method for optical coherence tomography angiography in ophthalmology.

PURPOSE: The optic disc and the macular are two major anatomical structures in the human eye. Optic ...

Perception of Robotics and Navigation by Spine Fellows and Early Attendings: The Impact of These Technologies on Their Training and Practice.

BACKGROUND: There is scant data on the role that robotics and navigation play in spine surgery train...

Convolutional-neural-network-based radiographs evaluation assisting in early diagnosis of the periodontal bone loss via periapical radiograph.

BACKGROUND/PURPOSE: The preciseness of detecting periodontal bone loss is examiners dependent, and t...

A 48-Year-Old Man With a Hip Fracture and Skin Rash: A Case Report.

BACKGROUND/OBJECTIVE: Patients with systemic mastocytosis are at high risk of developing osteoporosi...

The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning.

PURPOSE: Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelera...

Large language models: Are artificial intelligence-based chatbots a reliable source of patient information for spinal surgery?

PURPOSE: Large language models (LLM) have recently attracted attention because of their enormous per...

Performance of deep learning models for response evaluation on whole-body bone scans in prostate cancer.

OBJECTIVE: We aimed to develop deep learning classifiers for assessing therapeutic response on bone ...

Utility of deep learning for the diagnosis of cochlear malformation on temporal bone CT.

OBJECTIVE: Diagnosis of cochlear malformation on temporal bone CT images is often difficult. Our aim...

Automated Orientation and Registration of Cone-Beam Computed Tomography Scans.

Automated clinical decision support systems rely on accurate analysis of three-dimensional (3D) medi...

Molecular Joint Representation Learning via Multi-Modal Information of SMILES and Graphs.

In recent years, artificial intelligence has played an important role on accelerating the whole proc...

Attenuative effects of collagen peptide from milkfish () scales on ovariectomy-induced osteoporosis.

Osteoporosis is characterized by low bone mass, bone microarchitecture disruption, and collagen loss...

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery.

This article presents a novel extensible continuum robot (ECR) with growing motion capability for im...

Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach.

In the field of environmental science, traditional methods for predicting PM2.5 concentrations prima...

Preclinical validation of a novel deep learning-based metal artifact correction algorithm for orthopedic CT imaging.

PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, n...

Pelphix: Surgical Phase Recognition from X-ray Images in Percutaneous Pelvic Fixation.

Surgical phase recognition (SPR) is a crucial element in the digital transformation of the modern op...

CURRENT NEURAL NETWORKS DEMONSTRATE POTENTIAL IN AUTOMATED CERVICAL VERTEBRAL MATURATION STAGE CLASSIFICATION BASED ON LATERAL CEPHALOGRAMS.

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Neural networks for classification of cervical vertebra...

Automatic orbital segmentation using deep learning-based 2D U-net and accuracy evaluation: A retrospective study.

The purpose of this study was to verify whether the accuracy of automatic segmentation (AS) of compu...

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