AIMC Topic: Radiography

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An interpretable deep learning model for hallux valgus prediction.

Computers in biology and medicine
BACKGROUND: This work developed an interpretable deep learning model to automatically annotate landmarks and calculate the hallux valgus angle (HVA) and the intermetatarsal angle (IMA), reducing the time and error of manual calculations by medical ex...

Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

BMJ open
INTRODUCTION: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial ...

Advances in Artificial Intelligence for automated knee osteoarthritis classification using the IKDC system.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
INTRODUCTION: Knee osteoarthritis is one of the most prevalent and debilitating musculoskeletal diseases, with a high incidence among the elderly population. Early detection and accurate classification can improve clinical outcomes for affected patie...

Machine learning is better than surgeons at assessing unicompartmental knee replacement radiographs.

The Knee
BACKGROUND: Poor results occasionally occur after unicompartmental knee replacement (UKR). It is often difficult, even for experienced surgeons, to determine why patients have poor outcomes from radiographs. The aim was to compare the ability of expe...

Leveraging AI models for lesion detection in osteonecrosis of the femoral head and T1-weighted MRI generation from radiographs.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
This study emphasizes the importance of early detection of osteonecrosis of the femoral head (ONFH) in young patients on long-term glucocorticoid therapy, including those with acute lymphoblastic leukemia, lupus, and other diagnoses. While X-ray and ...

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoarthritis (OA). Knee OA is commonly associated with varus deformity, where the alignment of the knee ...

Comparative assessment of three AI platforms in answering USMLE Step 1 anatomy questions or identifying anatomical structures on radiographs.

Clinical anatomy (New York, N.Y.)
The application of artificial intelligence (AI) in education has gained great attention recently. Integration of AI tools in anatomy teaching is currently engaging researchers and academics worldwide. Several AI chatbots have been generated, the most...

Application of Machine Learning to Osteoporosis and Osteopenia Screening Using Hand Radiographs.

The Journal of hand surgery
PURPOSE: Fragility fractures associated with osteoporosis and osteopenia are a common cause of morbidity and mortality. Current methods of diagnosing low bone mineral density require specialized dual x-ray absorptiometry (DXA) scans. Plain hand radio...

Artificial intelligence in fracture detection on radiographs: a literature review.

Japanese journal of radiology
Fractures are one of the most common reasons of admission to emergency department affecting individuals of all ages and regions worldwide that can be misdiagnosed during radiologic examination. Accurate and timely diagnosis of fracture is crucial for...

Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip.

BMC musculoskeletal disorders
OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radio...