Orthopedics

Deep learning ensemble for abdominal aortic calcification scoring from lumbar spine X-ray and DXA images

Abdominal aortic calcification (AAC) is an independent predictor of cardiovascular diseases (CVDs). AAC is typically detected as an incidental finding in spine scans. Early detection of AAC through opportunistic screening using any available imaging modalities could help identify individuals with a higher risk of developing clinical CVDs. However, AAC is not routinely assessed in clinics, and manu...

The gSOS Polygenic Score is Associated with Bone Density and Fracture Risk in Childhood

The polygenic risk score genetic quantitative ultrasound speed of sound (gSOS) was developed using machine learning algorithms in adults of European ancestry and associates with reduced odds of fracture in adults. We aimed to determine if gSOS was associated with bone health in children. Two observational studies of children were evaluated: (1) children enrolled in the Bone Mineral Density in Chil...

Deep learning clarifies association of osteoporosis risk with bone metastasis in premenopausal women after surgery for early-stage breast cancer: a multicenter retrospective cohort study

Adjuvant use of bone-modifying agents (BMAs) to early-stage breast cancer (eBC) aims to maintain bone density, leading to prevention of bone metastasi...

Robust radiomic signatures of intervertebral disc degeneration from MRI

Low back pain (LBP) is the most common musculoskeletal symptom worldwide and intervertebral disc (IVD) degeneration is an important contributing facto...

Enhancing Glaucoma Detection through Supervised Pre-training with Intermediate Phenotypes: A Multi-Institutional Study

Glaucoma is a leading cause of irreversible blindness worldwide, with early diagnosis often hindered by subtle symptomatology and the lack of comprehe...

Datasheet for the IDHea Primary Eye Care Dataset: A Real-World Ocular Imaging Resource for Research

Real-world ocular imaging datasets are essential for advancing research in artificial intelligence (AI), autonomous disease screening, and clinical de...

USING ARTIFICIAL INTELLIGENCE TO PREDICT TREATMENT OUTCOMES IN PATIENTS WITH NEUROGENIC OVERACTIVE BLADDER AND MULTIPLE SCLEROSIS

Many women with multiple sclerosis (MS) experience neurogenic overactive bladder (NOAB) characterized by urinary frequency, urinary urgency and urgenc...

Beyond Benchmarks: Towards Robust Artificial Intelligence Bone Segmentation in Socio-Technical Systems

Despite the advances in automated medical image segmentation, AI models still underperform in various clinical settings, challenging real-world integr...

Deep Learning-Based Opportunistic CT Osteoporosis Screening and Establishment of Normative Values

Osteoporosis is underdiagnosed and undertreated prompting the exploration of opportunistic screening using CT and artificial intelligence (AI). To dev...

Exploring Novel Biomarkers for Early Detection of Osteoporosis

Osteoporosis is characterized by diminished BMD and deteriorated bone microstructure, significantly increasing fracture susceptibility. This study lev...

Clinician-Led Code-Free Deep Learning for Detecting Papilloedema and Pseudopapilloedema Using Optic Disc Imaging

Differentiating pseudopapilloedema from papilloedema is challenging, but critical for prompt diagnosis and to avoid unnecessary invasive procedures. F...

CMANet: Cross-Modal Attention Network for 3-D Knee MRI and Report-Guided Osteoarthritis Assessment

Knee osteoarthritis (OA) is a leading cause of disability worldwide, with early identification of structural changes critical for improving patient ou...

Joint associations of device-measured physical activity and sleep duration with incident major adverse cardiovascular events: prospective analysis of the UK Biobank

The interaction between physical activity and sleep with cardiovascular disease remains poorly understood, despite both being key risk factors. This s...

Development of a novel musculoskeletal hypothesis using sparse Group Factor Analysis: the ADVANCE cohort

Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing long-term musculoskeletal health, particularly follow...

Comparison of Foundation and Supervised Learning-Based Models for Detection of Referable Glaucoma from Fundus Photographs

To compare the performance of a foundation model and a supervised learning-based model for detecting referable glaucoma from fundus photographs. Evalu...

Decoding phantom limb movements from intraneural recordings

Limb loss leads to severe sensorimotor deficits and requires the use of a prosthetic device, especially in lower-limb amputees. While direct recording...

Large Language Models for Zero-Shot Procedure Extraction in Orthopedic Surgery: A Comparative Evaluation

Operative notes in electronic health records contain critical information for understanding surgical care, yet manual coding is time-consuming, costly...

Deep Learning-Assisted Skeletal Muscle Radiation Attenuation at C3 Predicts Survival in Head and Neck Cancer

Head and neck cancer (HNC) patients face an increased risk of malnutrition due to lifestyle, tumor localization, and treatment effects. While skeletal...

Machine learning algorithm to predict fragility fractures and identification of important features – an explainable approach

In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites. We inve...

Integrating BERT and Graph Convolutional Networks for Medical Literature Mining: A Knowledge Graph Ap-proach to Pelvic Fracture Research Analysis

Pelvic fractures have consistently been a focal point in orthopedic research. This study aims to provide a comprehensive analysis of the literature on...