AIMC Topic: Fractures, Bone

Clear Filters Showing 131 to 140 of 187 articles

Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Comm...

Sanders classification of calcaneal fractures in CT images with deep learning and differential data augmentation techniques.

Injury
BACKGROUND: Classification of the type of calcaneal fracture on CT images is essential in driving treatment. However, human-based classification can be challenging due to anatomical complexities and CT image constraints. The use of computer-aided cla...

Indirect visual guided fracture reduction robot based on external markers.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Traditional fracture reduction surgery cannot ensure the accuracy of the reduction while consuming the physical strength of the surgeon. Although monitoring the fracture reduction process through radiography can improve the accuracy of th...

Robot-assisted double screw fixation of minimally displaced scaphoid waist fracture nonunions or delayed unions without bone graft.

The Journal of hand surgery, European volume
We retrospectively reviewed 12 minimally displaced fractures of the scaphoid waist in 12 patients who developed delayed or nonunions with or without conservative treatment. Mean time between injury and surgery was 6 months (range 3-12). The fractures...

Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men.

Calcified tissue international
The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Stud...

Diagnostic accuracy of deep learning in orthopaedic fractures: a systematic review and meta-analysis.

Clinical radiology
AIM: To gather and compare related clinical studies, and to investigate the accuracy and reliability of deep learning in detecting orthopaedic fractures.

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This study reports the development of an artificial neural network computation model to predict the accumulation of crack density and crack length in cancellous bone under a cyclic load. The model was then applied to conduct a parametric investigatio...

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect a...

Deep learning in fracture detection: a narrative review.

Acta orthopaedica
Artificial intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI, particularly deep learning, has recently made substantial strides in perception tasks allowing machin...