AIMC Topic: Osteoarthritis, Knee

Clear Filters Showing 91 to 100 of 255 articles

Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data, and Symptomatic Assessments.

Methods of information in medicine
OBJECTIVE: In this study, we propose a novel framework that utilizes deep learning and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of 7 years.

Development of an automatic surgical planning system for high tibial osteotomy using artificial intelligence.

The Knee
BACKGROUND: This study proposed an automatic surgical planning system for high tibial osteotomy (HTO) using deep learning-based artificial intelligence and validated its accuracy. The system simulates osteotomy and measures lower-limb alignment param...

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis.

Journal of orthopaedic surgery and research
BACKGROUND: For knee osteoarthritis patients, analyzing alignment of lower limbs is essential for therapy, which is currently measured from standing long-leg radiographs of anteroposterior X-ray (LLR) manually. To address the time wasting, poor repro...

Deep Convolutional Neural Network for Dedicated Regions-of-Interest Based Multi-Parameter Quantitative Ultrashort Echo Time (UTE) Magnetic Resonance Imaging of the Knee Joint.

Journal of imaging informatics in medicine
We proposed an end-to-end deep learning convolutional neural network (DCNN) for region-of-interest based multi-parameter quantification (RMQ-Net) to accelerate quantitative ultrashort echo time (UTE) MRI of the knee joint with automatic multi-tissue ...

Automated analysis of knee joint alignment using detailed angular values in long leg radiographs based on deep learning.

Scientific reports
Malalignment in the lower limb structure occurs due to various causes. Accurately evaluating limb alignment in situations where malalignment needs correction is necessary. To create an automated support system to evaluate lower limb alignment by quan...

Predicting the onset of end-stage knee osteoarthritis over two- and five-years using machine learning.

Seminars in arthritis and rheumatism
OBJECTIVE: Identifying participants who will progress to advanced stage in knee osteoarthritis (KOA) trials remains a significant challenge. Current tools, relying on total knee replacements (TKR), fall short in reliability due to the extraneous fact...

Development of a machine learning model for identifying the optimal situation favoring double-level osteotomy over single-level high tibial osteotomy.

The Knee
BACKGROUND: This study aimed to develop a machine learning (ML) model to identify the optimal situation wherein double-level osteotomy (DLO) is favored for severe varus knees by analyzing unfavorable outcomes. This study hypothesized that there are t...

Prediction of postoperative gait speed change after bilateral primary total knee arthroplasty in female patients using a machine learning algorithm.

Orthopaedics & traumatology, surgery & research : OTSR
BACKGROUND: An important aim of total knee arthroplasty is to achieve functional recovery, which includes post-operative increase in walking speed. Therefore, predicting whether a patient will walk faster or slower after surgery is important in TKA, ...

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Elderly patients often have more than one disease that affects walking behavior. An objective tool to identify which disease is the main cause of functional limitations may aid clinical decision making. Therefore, we investigated whether gait pattern...