Orthopedics

TransformDDI: The Transformer-Based Joint Multi-Task Model for End-to-End Drug-Drug Interaction Extraction.

Drug-Drug Interactions (DDI) identification is a part of the drug safety process, that focuses at av...

Human Phenotype Ontology Annotations for Rare Congenital Conditions: Application to Arthrogryposis Multiplex Congenita.

Arthrogryposis multiplex congenita (AMC) represents a large, rare group of congenital conditions. Th...

Redefining Value in Orthopedic Surgery.

Value-based health care is a commonly used term that merits a strong understanding from the orthoped...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classificatio...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidne...

A new approach to bioceramics based on tissue reaction of tricalcium phosphate for biomedical and sport applications using machine learning modeling.

Tricalcium phosphate (TCP) bioceramics have emerged as a promising option to meet the specific requi...

Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.

PURPOSE: To evaluate the usefulness of radiomics features extracted from ultrasonographic images in ...

Therapeutic potential of allosteric HECT E3 ligase inhibition.

Targeting ubiquitin E3 ligases is therapeutically attractive; however, the absence of an active-site...

Forecasting motion trajectories of elbow and knee joints during infant crawling based on long-short-term memory (LSTM) networks.

BACKGROUND: Hands-and-knees crawling is a promising rehabilitation intervention for infants with mot...

Deep Learning-Based Reconstruction for Accelerated Cervical Spine MRI: Utility in the Evaluation of Myelopathy and Degenerative Diseases.

BACKGROUND AND PURPOSE: Deep learning (DL)-based reconstruction enables improving the quality of MR ...

The future outlook for data in orthopedic surgery: A new era of real-time innovation.

The orthopedic field is on the brink of a significant transformation-a shift from retrospective anal...

Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging.

In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical...

Effectiveness of an intelligent weight-bearing rehabilitation robot in enhancing recovery following anterior cruciate ligament reconstruction.

AIM: Orthopedic surgery patients frequently delay early rehabilitation due to postoperative discomfo...

Can we use lower extremity joint moments predicted by the artificial intelligence model during walking in patients with cerebral palsy in the clinical gait analysis?

Several studies have highlighted the advantages of employing artificial intelligence (AI) models in ...

[Research progress of effect mechanism of acupotomy for knee osteoarthritis].

Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After re...

Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis.

The worldwide prevalence of glaucoma makes it a major reason for blindness thus proper early diagnos...

Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women.

The aim of this study was to establish the optimal prediction model by comparing the prediction effe...

Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis.

The management of skeletal-related events (SREs), particularly the prevention of pathological fractu...

Development and validation of a nomogram for predicting bone marrow involvement in lymphoma patients based on F-FDG PET radiomics and clinical factors.

OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and cli...

In reply to the Letter to Editor regarding Comment on: Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review.

Comment On: "Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review".