Orthopedics

Preoperative MRI-Derived Navigation Reduces Radiation Exposure in Pediatric Spinal Fusion.

BACKGROUND: Minimizing radiation exposure during pediatric spinal deformity correction is critical due to the cumulative lifetime effects of ionizing radiation. This study uses preoperative MRI-derived synthetic CT data to potentially eliminate preoperative CT scans entirely and reduce the overall radiation load on patients undergoing spinal fusion for adolescent idiopathic scoliosis (AIS). METHOD...

Integrative analysis of single-cell and bulk RNA sequencing data using machine learning identifies PTGDS as a key subsynovial fibroblast gene in osteoarthritis.

Filament sensing tension: A bionic artificial tendon for self-force-regulated artificial muscle-driven wearable robotics.

Artificial muscles have been in development for decades and play a crucial role in the field of wearable robotics. However, a universal device for bot...

Opportunistic Screening on Chest CT, From the AJR Special Series on Screening.

The increase in chest CT volumes affords radiologists the opportunity to systematically assess imaging biomarkers, including coronary and thoracic art...

Predicting minimal clinically important difference after hip arthroscopy: logistic regression versus machine learning.

PURPOSE: Hip arthroscopy outcomes for femoroacetabular impingement (FAI) remain heterogeneous, with 30-40% of patients failing to achieve meaningful i...

Letter to the Editor: Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients.

Actor-Critic-Based Prescribed Performance Optimal Control for Flexible-Joint Robots With Input Delay.

This article presents a prescribed performance optimal control method for flexible-joint (FJ) robots with input delay. First, an auxiliary system and ...

Automated quantification of coronal balance in spinal deformity: a safety-aware clinical workflow.

The assessment of coronal balance is critical for cosmetic appearance and quality of life in patients with adolescent idiopathic scoliosis (AIS), yet ...

Assessing predictive accuracy of 2D digital templating in fluoroscopy-guided direct anterior approach total hip arthroplasty.

INTRODUCTION: Preoperative 2D digital templating aids surgical planning in total hip arthroplasty (THA). We evaluated template accuracy by comparing p...

Prediction of on-field rugby scrummaging contact forces from videos using artificial neural networks.

Rugby is a contact sport with a high risk of injury. Scrums are a key component of the game and represent a collision event associated with serious in...

Three-Dimensional human motion analysis using LiDAR technology: A systematic review.

3D Light Detection and Ranging (LiDAR) has gained increasing attention in the field of human motion analysis due to its capability to non-invasively c...

Artificial intelligence in ACL injury prediction and prevention: a systematic review.

BACKGROUND: Anterior cruciate ligament (ACL) injuries are prevalent in sports, with significant physical, economic, and long-term health impacts. Arti...

Medical image pretraining-based transfer learning for generalizable and robust diagnosis of bone tumors on radiographs: a multi-center study.

OBJECTIVES: To develop a generalizable and robust deep learning model for bone tumor classification in radiographs by leveraging domain-specific medic...

Optimizing the management of periprosthetic infections with artificial intelligence: current evidence and future directions.

Periprosthetic joint infections (PJIs) are a serious complication in both primary arthroplasty and revision arthroplasty, posing a major challenge in ...

Comment on "Artificial intelligence-driven 3D surface-topography app for screening and monitoring adolescent scoliosis: early results from a single institution".

Demystifying machine learning approaches in digital bone imaging using microCT and HRpQCT.

Micro-computed tomography (microCT) and high-resolution peripheral quantitative computed tomography (HRpQCT) generate three-dimensional digital images...

Integrating Machine Learning into Fracture Liaison Services: Toward precision risk stratification in osteoporosis care: A prospective cohort study.

BACKGROUND: Traditional fracture risk assessment tools have limitations in accurately predicting re-fracture risk. Machine learning (ML) approaches of...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model. PURPOSE: To develop novel AI software for early ...

Machine Learning to Predict Remission Between Six and 24 Months in Rheumatoid Arthritis: Insights from the JAK-pot Collaboration.

OBJECTIVE: To develop, externally validate, and simplify a machine-learning (ML) model to predict remission between six and 24 months in rheumatoid ar...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...