AIMC Topic: Hip Fractures

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Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis.

JAMA network open
IMPORTANCE: Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown.

Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review.

Journal of orthopaedic surgery and research
BACKGROUND: In the emergency room, clinicians spend a lot of time and are exposed to mental stress. In addition, fracture classification is important for determining the surgical method and restoring the patient's mobility. Recently, with the help of...

Recognition and Segmentation of Individual Bone Fragments with a Deep Learning Approach in CT Scans of Complex Intertrochanteric Fractures: A Retrospective Study.

Journal of digital imaging
The characteristics of bone fragments are the main influencing factors for the choice of treatment in intertrochanteric fractures. This study aimed to develop a deep learning algorithm for recognizing and segmenting individual fragments in CT images ...

Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.

BMC geriatrics
BACKGROUND: Fragility hip fracture increases morbidity and mortality in older adult patients, especially within the first year. Identification of patients at high risk of death facilitates modification of associated perioperative factors that can red...

The Kocher-Langenbeck approach combined with robot-aided percutaneous anterior column screw fixation for transverse-oriented acetabular fractures: a retrospective study.

BMC musculoskeletal disorders
OBJECTIVE: Transverse-oriented acetabular fractures (TOAFs), including transverse, transverse with posterior wall and T-shaped fractures, are always challenging for double-column reduction and fixation with minimally invasive method. The purpose of t...

Machine learning outperforms clinical experts in classification of hip fractures.

Scientific reports
Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population ageing, the number of incident hip fractures is predicted to increase globally. As fracture classificat...

X-Ray Film under Artificial Intelligence Algorithm in the Evaluation for Nursing Effect of Gamma Nail Internal Fixation in Elderly Patients with Intertrochanteric Fracture of Femur.

Computational and mathematical methods in medicine
The aim of this work was to explore the effects of Gamma nail internal fixation for intertrochanteric fracture of femur by X-ray film classification and recognition method based on artificial intelligence algorithm. The study subjects were 100 elderl...

Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning.

Nature communications
Dual-energy X-ray absorptiometry (DXA) is underutilized to measure bone mineral density (BMD) and evaluate fracture risk. We present an automated tool to identify fractures, predict BMD, and evaluate fracture risk using plain radiographs. The tool pe...

Deep Learning in the Detection of Rare Fractures - Development of a "Deep Learning Convolutional Network" Model for Detecting Acetabular Fractures.

Zeitschrift fur Orthopadie und Unfallchirurgie
BACKGROUND: Fracture detection by artificial intelligence and especially Deep Convolutional Neural Networks (DCNN) is a topic of growing interest in current orthopaedic and radiological research. As learning a DCNN usually needs a large amount of tra...