AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cartilage

Showing 1 to 10 of 25 articles

Clear Filters

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.

Journal of biomechanics
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual s...

A More Posterior Tibial Tubercle (Decreased Sagittal Tibial Tubercle-Trochlear Groove Distance) Is Significantly Associated With Patellofemoral Joint Degenerative Cartilage Change: A Deep Learning Analysis.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To perform patellofemoral joint (PFJ) geometric measurements on knee magnetic resonance imaging scans and determine their relations with chondral lesions in a multicenter cohort using deep learning.

Applications of Computer Modeling and Simulation in Cartilage Tissue Engineering.

Tissue engineering and regenerative medicine
BACKGROUND: Advances in cartilage tissue engineering have demonstrated noteworthy potential for developing cartilage for implantation onto sites impacted by joint degeneration and injury. To supplement resource-intensive in vivo and in vitro studies ...

Endoscopic autologous cartilage injection for the patulous eustachian tube.

American journal of otolaryngology
Patulous eustachian tube (PET) can have a significant negative impact on a patient's quality of life. Several methods of surgical management can be an option to treat PET, and our objective is to evaluate the safety and efficacy of autologous cartila...

Coefficient of Friction Patterns Can Identify Damage in Native and Engineered Cartilage Subjected to Frictional-Shear Stress.

Annals of biomedical engineering
The mechanical loading environment encountered by articular cartilage in situ makes frictional-shear testing an invaluable technique for assessing engineered cartilage. Despite the important information that is gained from this testing, it remains un...

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data.

BMC genomics
BACKGROUND: Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machin...

Automatic Grading Assessments for Knee MRI Cartilage Defects via Self-ensembling Semi-supervised Learning with Dual-Consistency.

Medical image analysis
Knee cartilage defects caused by osteoarthritis are major musculoskeletal disorders, leading to joint necrosis or even disability if not intervened at early stage. Deep learning has demonstrated its effectiveness in computer-aided diagnosis, but it i...

Resolving complex cartilage structures in developmental biology via deep learning-based automatic segmentation of X-ray computed microtomography images.

Scientific reports
The complex shape of embryonic cartilage represents a true challenge for phenotyping and basic understanding of skeletal development. X-ray computed microtomography (μCT) enables inspecting relevant tissues in all three dimensions; however, most 3D m...

A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images.

Computers in biology and medicine
OBJECTIVE: Rheumatoid arthritis (RA) is a chronic disease characterized by erosive symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease. Cartilage damage is one of the most relevant determinants of physical disabil...