AIMC Topic: Osteoarthritis, Knee

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Classification of Grades of Subchondral Sclerosis from Knee Radiographic Images Using Artificial Intelligence.

Sensors (Basel, Switzerland)
Osteoarthritis (OA) is the most common joint disease, affecting over 300 million people worldwide. Subchondral sclerosis is a key indicator of OA. Currently, the diagnosis of subchondral sclerosis is primarily based on radiographic images; however, r...

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

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After reviewing systematically the mechanism studies on acupotomy for KOA over the past 5 years, It is revealed that acupotomy synergistically intervenes in t...

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during...

ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs.

IEEE transactions on medical imaging
Analyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance ...

Posttraumatic Arthritis After Anterior Cruciate Ligament Injury: Machine Learning Comparison Between Surgery and Nonoperative Management.

The American journal of sports medicine
BACKGROUND: Nonoperative and operative management techniques after anterior cruciate ligament (ACL) injury are both appropriate treatment options for selected patients. However, the subsequent development of posttraumatic knee osteoarthritis (PTOA) r...

A machine learning approach using gait parameters to cluster TKA subjects into stable and unstable joints for discovery analysis.

The Knee
BACKGROUND: Patient-reported joint instability after total knee arthroplasty (TKA) is difficult to quantify objectively. Here, we apply machine learning to cluster TKA subjects using nine literature-proposed gait parameters as knee instability predic...

AI classification of knee prostheses from plain radiographs and real-world applications.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...

Advance signal processing and machine learning approach for analysis and classification of knee osteoarthritis vibroarthrographic signals.

Medical engineering & physics
Osteoarthritis is a common cause of disability among elderly significantly affecting their quality of life due to pain and functional limitations. This study proposes a novel, non-invasive, and cost-effective diagnostic technique using vibroarthrogra...

An explainable machine learning-based prediction model for sarcopenia in elderly Chinese people with knee osteoarthritis.

Aging clinical and experimental research
BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disease that leads to loss of muscle mass and function, resulting in adverse health outcomes such as falls, functional decline, and death. Knee osteoarthritis (KOA) is a common chro...

Measuring the severity of knee osteoarthritis with an aberration-free fast line scanning Raman imaging system.

Analytica chimica acta
Osteoarthritis (OA) is a major cause of disability worldwide, with symptoms like joint pain, limited functionality, and decreased quality of life, potentially leading to deformity and irreversible damage. Chemical changes in joint tissues precede ima...