Orthopedics

Joint modelling of brain and behaviour dynamics with artificial intelligence.

Artificial intelligence has created tremendous advances for many scientific and engineering applications. In this Review, we synthesize recent advances in joint brain-behaviour modelling of neural and behavioural data, with a focus on methodological innovations, scientific and technical motivations, and key areas for future innovation. We discuss how these tools reveal the shared structure between...

Joint Associations of Type D Personality and Allostatic Load With Coronary Artery Disease in Type 2 Diabetes: Evaluating the Role of Allostatic Load.

OBJECTIVE: This study aimed to (1) evaluate and compare the independent associations and predictive strength of type D personality and allostatic load (AL) against traditional risk factors for coronary artery disease (CAD) in patients with type 2 diabetes (T2DM), (2) explore the potential mediating role of AL in the association between type D personality and CAD, and (3) investigate their joint ef...

Programmable materials: A comprehensive review on shape memory polymers for orthopedic applications.

Shape memory polymers (SMP) are smart, active polymers, which can significantly change their properties by external stimuli such as heat or temperatur...

Bot vs. doc-who is better at reading proximal humerus fracture x-rays?

BACKGROUND: Artificial intelligence is becoming increasingly utilized as a source of convenient, efficient, and cost-effective information. Considerin...

A comparative study of the interpretation results of different artificial intelligence bone age assessment software.

OBJECTIVES: To compare the interpretation results of different AI bone age assessment software using the TW3 (Tanner-Whitehouse 3) method. METHODS: Th...

Enhancing vertebral fracture prediction using multitask deep learning computed tomography imaging of bone and muscle.

OBJECTIVES: To develop and externally validate a computed tomography (CT)-based multitask learning model to predict fracture risk. MATERIALS AND METHO...

Development of an explainable machine learning model to reproduce and interpret expert pharmacological decisions in osteoporosis treatment.

The management of osteoporosis in real-world clinical practice is highly heterogeneous, reflecting the complexity and variability inherent in therapeu...

Unveiling CDKN1A and RELA: Machine learning-driven aging biomarkers for precision diagnosis and therapy in knee osteoarthritis.

BACKGROUND: Knee Osteoarthritis (KOA) is a degenerative joint disease marked by progressive cartilage deterioration, closely tied to cellular senescen...

Retrieval-augmented ChatGPT-4o improves accuracy but reduces readability in hip arthroscopy patient education.

PURPOSE: To compare the accuracy, readability and patient-centeredness of responses generated by standard ChatGPT-4o and its retrieval-augmented 'deep...

The appropriateness of primary care physician referrals for lumbar spine magnetic resonance imaging (MRI): retrospective cross-sectional study.

AIM: Low back pain (LBP) affects a significant proportion of the population. There has been an increase in referrals for magnetic resonance imaging (M...

The evolving landscape of screening, management and treatment strategies of aortic stenosis in ATTR amyloidosis.

Transthyretin amyloid cardiomyopathy (ATTR-CM) and aortic stenosis (AS) frequently coexist in elderly patients, particularly men, creating a complex c...

Artificial Intelligence in Pediatric Surgery: From Diagnostics and Preoperative Planning to Risk Stratification: A Comprehensive Review of Current Applications.

OBJECTIVE: Artificial intelligence (AI) is increasingly explored in pediatric surgical care, yet its translation into diagnostics and preoperative pla...

Automated quality assurance of imaging dose and protocol adherence in computed tomography radiotherapy planning using TotalSegmentator-based segmentation.

PURPOSE: Computed tomography (CT) scans are vital for radiotherapy planning, providing essential data for dose calculations. This study retrospectivel...

Development and validation of a novel orthopedic blood use prediction model incorporating lab tests and thromboelastography.

OBJECTIVE: To develop and validate a prediction model integrating laboratory parameters and thromboelastography (TEG) for forecasting blood transfusio...

Peripapillary Choroidal Vascularity Index for Differentiating Papilledema from Pseudopapilledema: A Deep Learning-Based Approach.

PURPOSE: To compare the peripapillary choroidal vascularity index (PPCVI) in eyes with papilledema secondary to idiopathic intracranial hypertension (...

Global analysis of mineral aerosol and industrial effects on lake water quality using spectral indices and machine learning.

The complex physical and chemical interactions between desert mineral aerosol, industrial pollutants, and lake water during drought periods pose signi...

Role of artificial intelligence in veterinary anatomical diagnostics and zoonotic disease monitoring.

The use of artificial intelligence (AI) also playing a significant role in veterinary medicine due to the changing pattern of diseases in terms of cli...

Central similarity joint-learning for cross-domain retrieval.

Cross-domain retrieval holds significant research value in the field of image retrieval. However, existing cross-domain retrieval methods have the fol...

Deep Learning Model for Differentiating Between Neoplastic Pathologic Fracture and Nonpathologic Fracture Using Hip Radiographs.

BACKGROUND: Although radiographs are the first-line imaging modality, differentiating between neoplastic pathologic fractures and nonpathologic fractu...

Diagnostic performance of artificial intelligence for facial fracture detection: a systematic review.

OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI) models for detecting facial bone fractures on computed tomography (C...