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View article: Uncertainty Quantification of Central Canal Stenosis Deep Learning Classifier from Lumbar Sagittal T2-Weighted MRI
Uncertainty Quantification of Central Canal Stenosis Deep Learning Classifier from Lumbar Sagittal T2-Weighted MRI Open
Background Accurate assessment of the severity of central canal stenosis (CCS) on lumbar spine MRI is critical for clinical decision-making. We evaluated deep learning models for automated CCS grading on sagittal T2-weighted MRI, focusing …
View article: Simulating Federated Learning to Enable Multi‐Hospital Collaboration for Lumbopelvic Alignment Estimation
Simulating Federated Learning to Enable Multi‐Hospital Collaboration for Lumbopelvic Alignment Estimation Open
Background Accurate computation of radiological parameters related to spinal alignment is clinically crucial for diagnosing and managing conditions, such as adolescent idiopathic scoliosis and adult spinal deformities. Key parameters, incl…
View article: A data-driven analysis of lumbar steroid injection satisfaction in patients with chronic low back pain
A data-driven analysis of lumbar steroid injection satisfaction in patients with chronic low back pain Open
Chronic low back pain (CLBP) is a prevalent condition significantly reducing quality of life. Lumbar steroid injections are a widely used conservative treatment option, but their effectiveness varies among patients. This study aimed to dev…
View article: Automated radiographic assessment of lower limb alignment using deep learning in a data-constrained clinical setting
Automated radiographic assessment of lower limb alignment using deep learning in a data-constrained clinical setting Open
BACKGROUND: A model using stacked hourglass neural network modules was developed for automated lower limb alignment measurements in full-leg frontal radiographs. The goal was to assess whether high accuracy could be achieved with training …
View article: Chronic Low Back Pain Patient Satisfaction with Lumbar Steroid Injection: a Data-Driven Analysis
Chronic Low Back Pain Patient Satisfaction with Lumbar Steroid Injection: a Data-Driven Analysis Open
Chronic low back pain (CLBP) is a prevalent condition significantly reducing quality of life. Lumbar steroid injections are a widely used conservative treatment option, but their effectiveness varies among patients. This study aimed to dev…
View article: Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis
Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis Open
View article: Using deep learning to predict postoperative pain in reverse shoulder arthroplasty patients
Using deep learning to predict postoperative pain in reverse shoulder arthroplasty patients Open
View article: Methodological considerations in calculating the minimal clinically important change score for the core outcome measures index (COMI): insights from a large single-centre spine surgery registry
Methodological considerations in calculating the minimal clinically important change score for the core outcome measures index (COMI): insights from a large single-centre spine surgery registry Open
Introduction The Minimal Clinically Important Change (MCIC) is used in conjunction with Patient-Reported Outcome Measures (PROMs) to determine the clinical relevance of changes in health status. MCIC measures a change within the same perso…
View article: Advancing spine care through AI and machine learning: overview and applications
Advancing spine care through AI and machine learning: overview and applications Open
Machine learning (ML), a subset of artificial intelligence, is crucial for spine care and research due to its ability to improve treatment selection and outcomes, leveraging the vast amounts of data generated in health care for more accura…
View article: Image annotation and curation in radiology: an overview for machine learning practitioners
Image annotation and curation in radiology: an overview for machine learning practitioners Open
View article: Comparing image normalization techniques in an end-to-end model for automated modic changes classification from MRI images
Comparing image normalization techniques in an end-to-end model for automated modic changes classification from MRI images Open
View article: Automatic Calculation of Cervical Spine Parameters Using Deep Learning: Development and Validation on an External Dataset
Automatic Calculation of Cervical Spine Parameters Using Deep Learning: Development and Validation on an External Dataset Open
Study design Retrospective data analysis. Objectives This study aims to develop a deep learning model for the automatic calculation of some important spine parameters from lateral cervical radiographs. Methods We collected two datasets fro…
View article: Developing a new tool for scoliosis screening in a tertiary specialistic setting using artificial intelligence: a retrospective study on 10,813 patients: 2023 SOSORT award winner
Developing a new tool for scoliosis screening in a tertiary specialistic setting using artificial intelligence: a retrospective study on 10,813 patients: 2023 SOSORT award winner Open
View article: Automatic classification of the vertebral endplate lesions in magnetic resonance imaging by deep learning model
Automatic classification of the vertebral endplate lesions in magnetic resonance imaging by deep learning model Open
Introduction A novel classification scheme for endplate lesions, based on T2-weighted images from magnetic resonance imaging (MRI) scan, has been recently introduced and validated. The scheme categorizes intervertebral spaces as “normal,” …
View article: Commentary on “Predicting Mechanical Complications After Adult Spinal Deformity Operation Using a Machine Learning Based on Modified Global Alignment and Proportion Scoring With Body Mass Index and Bone Mineral Density”
Commentary on “Predicting Mechanical Complications After Adult Spinal Deformity Operation Using a Machine Learning Based on Modified Global Alignment and Proportion Scoring With Body Mass Index and Bone Mineral Density” Open
ISSN:2586-6583
View article: Artificial Intelligence Accurately Detects Traumatic Thoracolumbar Fractures on Sagittal Radiographs
Artificial Intelligence Accurately Detects Traumatic Thoracolumbar Fractures on Sagittal Radiographs Open
Background and Objectives: Commonly being the first step in trauma routine imaging, up to 67% fractures are missed on plain radiographs of the thoracolumbar (TL) spine. The aim of this study was to develop a deep learning model that detect…
View article: A fresh look at spinal alignment and deformities: Automated analysis of a large database of 9832 biplanar radiographs
A fresh look at spinal alignment and deformities: Automated analysis of a large database of 9832 biplanar radiographs Open
We developed and used a deep learning tool to process biplanar radiographs of 9,832 non-surgical patients suffering from spinal deformities, with the aim of reporting the statistical distribution of radiological parameters describing the s…
View article: Investigating How Reproducibility and Geometrical Representation in UMAP Dimensionality Reduction Impact the Stratification of Breast Cancer Tumors
Investigating How Reproducibility and Geometrical Representation in UMAP Dimensionality Reduction Impact the Stratification of Breast Cancer Tumors Open
Advances in next-generation sequencing have provided high-dimensional RNA-seq datasets, allowing the stratification of some tumor patients based on their transcriptomic profiles. Machine learning methods have been used to reduce and cluste…
View article: Correction to: Measuring the critical shoulder angle on radiographs: an accurate and repeatable deep learning model
Correction to: Measuring the critical shoulder angle on radiographs: an accurate and repeatable deep learning model Open
View article: Prediction of scoliosis severity from rasterstereographic image of the back surface by machine learning approach
Prediction of scoliosis severity from rasterstereographic image of the back surface by machine learning approach Open
View article: The Influence of Baseline Clinical Status and Surgical Strategy on Early Good to Excellent Result in Spinal Lumbar Arthrodesis: A Machine Learning Approach
The Influence of Baseline Clinical Status and Surgical Strategy on Early Good to Excellent Result in Spinal Lumbar Arthrodesis: A Machine Learning Approach Open
The study aims to create a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome using a machine learning (ML) approach. A single spine surgery …
View article: The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach
The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach Open
Aims To create, using a machine learning (ML) approach, a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome. Patients and Methods A single s…
View article: Accounting for Biomechanical Measures from Musculoskeletal Simulation of Upright Posture Does Not Enhance the Prediction of Curve Progression in Adolescent Idiopathic Scoliosis
Accounting for Biomechanical Measures from Musculoskeletal Simulation of Upright Posture Does Not Enhance the Prediction of Curve Progression in Adolescent Idiopathic Scoliosis Open
A major clinical challenge in adolescent idiopathic scoliosis (AIS) is the difficulty of predicting curve progression at initial presentation. The early detection of progressive curves can offer the opportunity to better target effective n…
View article: Automatic Diagnosis of Spinal Disorders on Radiographic Images: Leveraging Existing Unstructured Datasets With Natural Language Processing
Automatic Diagnosis of Spinal Disorders on Radiographic Images: Leveraging Existing Unstructured Datasets With Natural Language Processing Open
Study Design: Retrospective study. Objectives: Huge amounts of images and medical reports are being generated in radiology departments. While these datasets can potentially be employed to train artificial intelligence tools to detect findi…
View article: ARTIFICIAL INTELLIGENCE ACCURATELY DETECTS TRAUMATIC THORACOLUMBAR FRACTURES ON SAGITTAL RADIOGRAPHS
ARTIFICIAL INTELLIGENCE ACCURATELY DETECTS TRAUMATIC THORACOLUMBAR FRACTURES ON SAGITTAL RADIOGRAPHS Open
Background context Traumatic thoracolumbar (TL) fractures are frequently encountered in emergency rooms. Sagittal and anteroposterior radiographs are the first step in the trauma routine imaging. Up to 30% of TL fractures are missed in thi…
View article: 2-step deep learning model for landmarks localization in spine radiographs
2-step deep learning model for landmarks localization in spine radiographs Open
In this work we propose to use Deep Learning to automatically calculate the coordinates of the vertebral corners in sagittal x-rays images of the thoracolumbar spine and, from those landmarks, to calculate relevant radiological parameters …
View article: The importance of curve severity, type and instrumentation strategy in the surgical correction of adolescent idiopathic scoliosis: an in silico clinical trial on 64 cases
The importance of curve severity, type and instrumentation strategy in the surgical correction of adolescent idiopathic scoliosis: an in silico clinical trial on 64 cases Open
Adolescent idiopathic scoliosis is a three-dimensional deformity of the spine which is frequently corrected with the implantation of instrumentation with generally good or excellent clinical results; mechanical post-operative complications…
View article: Artificial intelligence can accurately and reliably detect traumatic thoracolumbar fractures on sagittal radiographs
Artificial intelligence can accurately and reliably detect traumatic thoracolumbar fractures on sagittal radiographs Open
View article: Image-based biomechanical models of the musculoskeletal system
Image-based biomechanical models of the musculoskeletal system Open
View article: The importance of curve severity, type and instrumentation strategy in the surgical correction of adolescent idiopathic scoliosis: an in silico clinical trial on 64 cases
The importance of curve severity, type and instrumentation strategy in the surgical correction of adolescent idiopathic scoliosis: an in silico clinical trial on 64 cases Open
Adolescent idiopathic scoliosis is a three-dimensional deformity of the spine which is frequently corrected with the implantation of instrumentation with generally good or excellent clinical results; mechanical post-operative complications…