Orthopedics

Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.

BACKGROUND: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.

Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.

Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, which is significant for improving patient prognosis. Based on the NHANES for the periods of 2011-2012, 2013-2014, and 2015-2016, the study involved 11,...

The use of machine learning for the prediction of response to follow-up in spine registries.

BACKGROUND: One of the main challenges in the maintenance of registries is to keep a high follow-up rate and a reliable strategy to limit dropout is c...

Novel transfer learning based bone fracture detection using radiographic images.

A bone fracture is a medical condition characterized by a partial or complete break in the continuity of the bone. Fractures are primarily caused by i...

Intelligent measurement of adolescent idiopathic scoliosis x-ray coronal imaging parameters based on VB-Net neural network: a retrospective analysis of 2092 cases.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) is a complex three-dimensional deformity, and up to now, there has been no literature reporting the ...

Perspectives surrounding robotic total hip arthroplasty: a cross-sectional analysis using natural language processing.

BACKGROUND: Robotic technology has been used in total hip arthroplasty (THA) for several years. Despite the advances in this field, perspectives surro...

Enhancing patient education on the role of tibial osteotomy in the management of knee osteoarthritis using a customized ChatGPT: a readability and quality assessment.

INTRODUCTION: Knee osteoarthritis (OA) significantly impacts the quality of life of those afflicted, with many patients eventually requiring surgical ...

OA-MEN: a fusion deep learning approach for enhanced accuracy in knee osteoarthritis detection and classification using X-Ray imaging.

BACKGROUND: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary scr...

Functional antimicrobial peptide-loaded 3D scaffolds for infected bone defect treatment with AI and multidimensional printing.

Infection is the most prevalent complication of fractures, particularly in open fractures, and often leads to severe consequences. The emergence of ba...

Exploring cultural imaginaries of robots with children with brittle bone disease: a participatory design study.

A symbiotic relationship exists between narrative imaginaries of and real-life advancements in technology. Such cultural imaginings have a powerful in...

Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.

Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medi...

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.

Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysi...

AutoSamp: Autoencoding k-Space Sampling via Variational Information Maximization for 3D MRI.

Accelerated MRI protocols routinely involve a predefined sampling pattern that undersamples the k-space. Finding an optimal pattern can enhance the re...

Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.

OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we cre...

Knee osteoarthritis severity detection using deep inception transfer learning.

Osteoarthritis (OA) is a prevalent condition resulting in physical limitations. Early detection of OA is critical to effectively manage this condition...

Advanced Three-Dimensional Assessment and Planning for Hallux Valgus.

The article discusses advanced three-dimensional evaluation of hallux valgus deformity using weightbearing computed tomography. Conventional two-dimen...

A new distal radius fracture classification depending on the specific fragments through machine learning clustering method.

PURPOSES: The objective of this study was to investigate intra-articular distal radius fractures, aiming to provide a comprehensive analysis of fractu...

Development and validation of machine learning algorithms for early detection of ankylosing spondylitis using magnetic resonance images.

BackgroundAnkylosing spondylitis (AS) is a chronic inflammatory disease affecting the sacroiliac joints and spine, often leading to disability if not ...

Detecting the articular disk in magnetic resonance images of the temporomandibular joint using YOLO series.

The purpose of this study was to construct an artificial intelligence object detection model to detect the articular disk from temporomandibular joint...

Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, ha...