Orthopedics

A novel interpretable classification of lumbar spinal stenosis using a cascade deep learning approach and T2-weighted MRI.

OBJECTIVE: Lumbar spinal stenosis (LSS) is a degenerative spinal condition characterized by the narrowing of the lumbar spinal canal, leading to back pain and disability. MRI remains the gold standard for LSS diagnosis, but diagnostic variability arises due to the lack of standardized imaging criteria. Recent advancements in artificial intelligence, particularly convolutional neural networks (CNNs...

Exploring the association between Frailty Index and Knee osteoarthritis in middle-aged and older Chinese adults: A cross-sectional analysis of data from the China Health and Retirement Longitudinal Study.

OBJECTIVE: To explore the relationship between Frailty Index (FI) and Knee osteoarthritis (KOA) in Chinese people aged 45 and above. METHODS: Data on symptomatic KOA, FI, and over ten covariates were from the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression and restricted cubic splines (RCS) were used to analyze the correlation. Subgroup and interaction analyses were al...

Wearable Devices and Artificial Intelligence to Enhance Perioperative Care in Total Knee Arthroplasty.

Rapidly evolving wearable devices have the potential to transform health care delivery and enhance outcomes. Applications of wearable smart devices ra...

[Construction of a prognostic assessment model of acupuncture intervention for lumbar disc herniation based on interpretable machine learning algorithms].

OBJECTIVE: To construct and validate a prognostic assessment model of acupuncture intervention for lumbar disc herniation (LDH), and analyze the key f...

Sagittal abdominal diameter and abdominal aortic calcification are associated with incident major adverse cardiovascular events: The Manitoba Bone Density Registry.

BACKGROUND: Sagittal abdominal diameter (SAD), a measure of visceral adiposity, has been linked to major adverse cardiovascular events (MACE). However...

Classification of anterior cruciate ligament injury profiles through running analysis: a machine learning approach.

Anterior cruciate ligament (ACL) injuries are common in athletes and often result in long-term complications such as altered gait and an increased ris...

Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank.

Scoliosis is the most common developmental spinal deformity, but its genetic underpinnings remain only partially understood. To identify scoliosis-rel...

Automating Adolescent Idiopathic Scoliosis Classification: An Interpretable, Workflow-Based Approach to Lenke Classification: Commentary on an article by Lingcong Xu, MD, et al.: "A Fully Automated Multistage Deep Learning System for Lenke Classification. Enhanced Diagnostic Precision in Adolescent Idiopathic Scoliosis".

DDS-UDA: Dual-domain synergy for unsupervised domain adaptation in joint segmentation of optic disc and optic cup.

Convolutional neural networks (CNNs) have achieved exciting performance in joint segmentation of optic disc and optic cup on single-institution datase...

Ultrastructural Evidence of Altered Dendritic Morphology in the Prefrontal Cortex of Alzheimer's Model Rats.

Alzheimer's disease (AD) is a neurodegenerative disorder with synaptic pathology as a core theme in aging-related research. Conventional imaging and l...

Clinical Feasibility of Deep Learning Contrast Synthesis From MR Fingerprinting in Knee Osteoarthritis.

BACKGROUND: Magnetic Resonance Fingerprinting (MRF) enables rapid quantitative parameter mapping from which synthetic clinical contrast images can be ...

Effectiveness of Thoracic Paravertebral Block in Minimally Invasive Vertebroplasty: A Retrospective Cohort Study Focusing on Pain Trajectories and Sagittal Spinal Alignment.

PURPOSE: To evaluate the effectiveness of ultrasound-guided thoracic paravertebral block (TPVB) combined with general anesthesia (GA) versus GA alone ...

Bone Metastasis Detection at CT with Deep Learning Models Trained Using Multicenter, Multimodal Reference Standards: Development and Evaluation.

Purpose To develop and validate deep learning models for detecting bone metastases on abdominal and thoracic CT scans, considering lesion visibility, ...

Hyperspectral imaging for orthopedic surgery: lightweight AI enables real-time bone and cartilage segmentation.

Long-term outcomes of lateral sinus floor elevation: A machine-learning analysis, systematic review, and meta-analysis of predictive factors.

OBJECTIVES: To quantify long-term (≥ 5 years) implant survival after lateral sinus floor elevation (LSFE) and to identify clinical predictors of long-...

Residual metric learning with class-specific consistency for multiclass classification.

Least squares regression (LSR) has been widely used in pattern recognition due to its concise form and ease of solution. However, inadequate explorati...

Establishment of a novel deep learning-based method for gait analysis after peripheral nerve injury in pigs.

BACKGROUND: Peripheral nerve injury with deficits has poor functional prognosis, making motor function assessment during nerve regeneration crucial. R...

EXPRESS: Identification of Acetylation-Related Molecular Signatures in Knee Osteoarthritis Patients with Significant Response to Warm-Needle Acupuncture Using Machine-Learning Approaches.

OBJECTIVE: This study aims to delineate remodeling effects of acetylation-related gene expression in knee osteoarthritis (KOA) patients markedly respo...

A vision transformer model for the detection of glaucoma from optic disc photographs.

This study uses a deep learning algorithm to analyze optic disc photographs (ODPs) and classify eyes as glaucomatous or healthy based on optic nerve a...

Predicting wear behavior of AZ31/TiC composites produced via ultrasonic vibration assisted friction stir processing using machine learning models.

This work aims to produce AZ31 Mg alloy reinforced with 15 vol.% TiC utilizing a unique Friction Stir mechanical vibration Processing (FSVP) technolog...