Orthopedics

Single-cell co-mapping reveals relationship between chromatin state and gene expression in early zebrafish development

Establishing a cell-type-specific chromatin landscape is crucial for the maintenance of cell identity during embryonic development. However, our knowledge of how this landscape is set during vertebrate embryogenesis has been limited, due to the lack of methods to jointly detect chromatin modifications and gene expression in the same cell. Here we present a multimodal measurement of full-length tra...

Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury

Early outcome prediction after acute traumatic spinal cord injury (SCI) is challenging due to pathological complexities and population heterogeneity. Routinely collected data during standard medical practice, such as laboratory analytics, can be a surrogate of underlying pathophysiological processes and used as a biomarker. We hypothesized that distinct temporal trends of blood analytics could be ...

Image-based Explainable Artificial Intelligence Accurately Identifies Myelodysplastic Neoplasms Beyond Conventional Signs of Dysplasia

Evaluation of bone marrow morphology by experienced hematologists is key in the diagnosis of myeloid neoplasms, especially to detect subtle signs of d...

Integrating Multidimensional Data Analytics for Precision Diagnosis of Chronic Low Back Pain

Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chronic (cLBP). Optimal diagnostic tools for cLBP remai...

Automated Segmentation of Trunk Musculature with a Deep CNN Trained from Sparse Annotations in Radiation Therapy Patients with Metastatic Spine Disease

Given the high prevalence of vertebral fractures post-radiotherapy in patients with metastatic spine disease, accurate and rapid muscle segmentation c...

Retinal vascularization rate predicts retinopathy of prematurity and remains unaffected by low-dose bevacizumab treatment

To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor...

Multimodal Deep Learning Model to Estimate CT-based Body Composition Measures Using Chest radiographs and Clinical Data

Body composition metrics such as visceral fat volume, subcutaneous fat volume and skeletal muscle volume, are important predictors for cardiovascular ...

Neural Networks Accurately Predict Precise Metrics of Hospital Resource Utilization for Total Hip Arthroplasty: A Retrospective Database Study

Total hip and knee arthroplasties (THAs and TKAs) are some of the most common and successful surgeries. Predicting their duration of surgery (DOS) and...

Identification of novel vertebral development factors through UK Biobank driven genetic and body imaging analysis reveals markers for back pain

Numerical variations and transitional anatomy in the human vertebral column, observed in up to 36% of individuals, represent a significant yet underst...

Evidence Based Gait Analysis Interpretation Tools (EB-GAIT)

Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. Th...

Six-Minute Knee MRI: A Comparison of Novel Approaches for Accelerated Imaging

Accelerated knee MRI protocols using deep learning (DL)-based reconstruction, 3D acquisitions, and parallel imaging can significantly reduce scan time...

CT-based Osteoporosis Classification and Bone-Muscle Interaction Mapping Using Multiple Interpretable Machine Learning Models with the BMINet Framework

Osteoporosis progresses through stages characterized by declining bone mineral density, vertebral deterioration, and muscle atrophy, with bone-muscle ...

Detecting papilloedema as a marker of raised intracranial pressure using artificial intelligence: a systematic review

Automated detection of papilloedema using artificial intelligence (AI) and retinal images acquired through an ophthalmoscope for triage of patients wi...

The influence of anatomical shape variations of wrist bones on kinematic parameter extraction in CT scans

Four-Dimensional Computed Tomography (4DCT) shows promise in diagnosing wrist pathologies such as scapholunate ligament lesions (SLL). Two parameters ...

Predicting Depression in Canadians with or at Risk of Diabetes: A Cross-Sectional Machine Learning Analysis

Depression often goes unrecognized in individuals at risk or living with diabetes, presenting considerable challenges for primary care clinicians. Alt...

RNAseq-Based Machine Learning Models for Prognostication of Multiple Myeloma

Multiple myeloma (MM) is characterized by abnormal plasma cell proliferation in the bone marrow, leading to symptoms like osteolytic lesions, anemia, ...

Automating Imaging Biomarker Analysis for Knee Osteoarthritis Using an Open-Source MRI-Based Deep Learning Pipeline

Osteoarthritis (OA) is a leading cause of chronic disability worldwide, with knee OA being the most prevalent form. Quantitative assessment of knee jo...

Spine age estimation using deep learning in lateral spine radiographs and DXA VFA to predict incident fracture and mortality

Spine age estimated from lateral spine radiographs and DXA vertebral fracture assessments (VFAs) could be associated with fracture and mortality risk....

Deep Learning Study of Alkaptonuria Spinal Disease Assesses Global and Regional Severity and Detects Occult Treatment Status

Deep learning (DL) is increasingly used to analyze medical imaging, but is less refined for rare conditions, which require novel pre-processing and an...

A CNN Autoencoder for Learning Latent Disc Geometry from Segmented Lumbar Spine MRI

Low back pain is the world’s leading cause of disability and pathology of the lumbar intervertebral discs is frequently considered a driver of pain. T...