Orthopedics

Letter to the Editor on Robot-Assisted Total Knee Arthroplasty Does Not Improve Long-Term Clinical and Radiologic Outcomes.

Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slow OA progression, but at later stages, only an invasive option is available: total knee replacement (TKR). Though a generally successful procedure, only 2/3 of patients who undergo the procedure report their knees feelin...

Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery.

BACKGROUND: Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumbar spine surgery; however, vascular injury has impl...

A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation.

PURPOSE: The purpose of this study is to evaluate the performance of a novel deep learning (DL) tool for fully automated measurements of the sagittal ...

Top-down machine learning approach for high-throughput single-molecule analysis.

Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events ofte...

Detection of hip osteoarthritis by using plain pelvic radiographs with deep learning methods.

OBJECTIVE: The incidence of osteoarthritis is gradually increasing in public due to aging and increase in obesity. Various imaging methods are used in...

Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) ...

Errors in femoral anteversion, femoral offset, and vertical offset following robot-assisted total hip arthroplasty.

The objectives were to determine errors in femoral anteversion (FA), femoral offset (FO), and vertical offset (VO) with robot-assisted total hip arthr...

Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition.

Understanding a person's feelings is a very important process for the affective computing. People express their emotions in various ways. Among them, ...

Intelligent analysis of coronal alignment in lower limbs based on radiographic image with convolutional neural network.

One of the first tasks in osteotomy and arthroplasty is to identify the lower limb varus and valgus deformity status. The measurement of a set of angl...

Femoral neck fracture detection in X-ray images using deep learning and genetic algorithm approaches.

OBJECTIVES: This study aims to detect frontal pelvic radiograph femoral neck fracture using deep learning techniques.

A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input.

PURPOSE: In cases of optic disc swelling, segmentation of projected retinal blood vessels from optical coherence tomography (OCT) volumes is challengi...

Optic Disc and Cup Image Segmentation Utilizing Contour-Based Transformation and Sequence Labeling Networks.

Optic disc (OD) and optic cup (OC) segmentation are important steps for automatic screening and diagnosing of optic nerve head abnormalities such as g...

Automatic optic nerve head localization and cup-to-disc ratio detection using state-of-the-art deep-learning architectures.

Computer vision has greatly advanced recently. Since AlexNet was first introduced, many modified deep learning architectures have been developed and t...

Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference.

OBJECTIVE: To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears.

Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

The medical and machine learning communities are relying on the promise of artificial intelligence (AI) to transform medicine through enabling more ac...

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study.

BACKGROUND: MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). However, there is currently no consensus as to how...

Multi-Person Pose Estimation Using an Orientation and Occlusion Aware Deep Learning Network.

Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skele...

Cervical vertebral maturation assessment on lateral cephalometric radiographs using artificial intelligence: comparison of machine learning classifier models.

OBJECTIVES: This study aimed to develop five different supervised machine learning (ML) classifier models using artificial intelligence (AI) technique...

An integrated deep learning framework for joint segmentation of blood pool and myocardium.

Simultaneous and automatic segmentation of the blood pool and myocardium is an important precondition for early diagnosis and pre-operative planning i...