Orthopedics

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 medical image pretraining. MATERIALS AND METHODS: This retrospective multi-center study included 2338 patients with histopathologically confirmed bone tumors from four centers. Four hundred seventy-one patients from one center were used for model developm...

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 orthopaedic surgery and creating a substantial financial burden. This literature review examines the current knowledge on PJI prediction, diagnosis and prognosis, with a focus on scoring systems and machine learning (ML) tools developed to improve th...

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

Multi-agent contrastive exploration via value decomposition discrepancy.

Value decomposition, as a factorization approach in multi-agent reinforcement learning (MARL), has been influential in the development of many effecti...

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...

Apoptotic extracellular vesicles act as master regulators of the bone healing niche.

Apoptotic extracellular vesicles (ApoEVs), natural bilayer nanoparticles released during programmed cell death, have emerged as pivotal regulators and...

Developing an artificial intelligence tool for detecting fractures of child abuse: preliminary findings.

OBJECTIVES: Approximately 6.9% of children in the United Kingdom have suffered physical abuse. Fractures are a common sign and must not be overlooked ...

From predictive accuracy to clinical utility: Model interpretability and the missing bone mineral density data.

This letter to the editor commends the study by Liu et al. on their machine learning model for predicting rib fractures but highlights two crucial cha...

Evaluating the accuracy and feasibility of a commercial AI-powered ergonomic assessment system for automotive assembly work.

Accurate ergonomic risk assessment is essential to prevent work-related musculoskeletal disorders. Artificial intelligence (AI) and computer vision of...

Computational models for predicting bone fracture healing: a review of modeling approaches, predictions, and emerging strategies.

BACKGROUND AND OBJECTIVE: The development of computational models for predicting bone fracture healing process holds strong potential to optimize ther...

Artificial intelligence in orthopedics: current applications, challenges, and future directions.

BACKGROUND: Artificial intelligence research in orthopedics has grown rapidly, yet a substantial gap remains between technical development and clinica...

Underperformance of Machine Learning Models Predicting Readmission and Prolonged Length of Stay Following Total Knee Arthroplasty Among Underrepresented Populations: Fairness Analysis and Mitigation Strategies.

BACKGROUND: While machine learning (ML) models demonstrate high predictive accuracy, recent studies reveal that ML models underperform for smaller sub...

Fuzzy-logic-driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds.

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-ligament) drive a need to design tissue engineering ...

Multimodal model integrating ultrasound and demographic data for the diagnosis of knee osteoarthritis.

Dynamic modulation of social gaze by sex and familiarity in marmoset dyads.

Social communication relies on the ability to perceive and interpret the direction of others' attention, and is commonly conveyed through head orienta...

An Intelligent Interactive Management Platform for Rheumatoid Arthritis Care: Real-World Observational Study.

BACKGROUND: Effective postdischarge management is essential for maintaining disease control and improving long-term outcomes in rheumatoid arthritis (...