Orthopedics

AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.

Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height prediction models, aiding in diagnosing spinal conditions like compression fractures and supporting individualized, sex-specific medicine. In this study an AI-...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans, but this approach introduces additional ionizing radiation and examination costs. To compare the effectiveness of MRI-based synthetic CT (sCT) in displaying lumbar degenerative changes, using CT as the gold standard. This prospective study was conducted between June 2021 and September 2023. Adult p...

CFM-UNet: coupling local and global feature extraction networks for medical image segmentation.

In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conv...

Formulation of low temperature mixed mode crack propagation behavior of crumb rubber modified HMA using artificial intelligence.

Determining mixed mode fracture parameters asphalt concrete mixtures remains an engineering challenge due to non-homogeneity and inelasticity of the m...

Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.

In this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parameters to assess the progressive loss of collagen an...

Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility.

OBJECTIVE: This study aimed to identify the hyoid bone (HB) using the nnU-Net based artificial intelligence (AI) model in cone beam computed tomograph...

Radiomics and machine learning for osteoporosis detection using abdominal computed tomography: a retrospective multicenter study.

OBJECTIVE: This study aimed to develop and validate a predictive model to detect osteoporosis using radiomic features and machine learning (ML) approa...

An interpretable machine learning approach for predicting and grading hip osteoarthritis using gait analysis.

BACKGROUND: Osteoarthritis (OA) of the hip is a progressive musculoskeletal disorder characterized by stiffness and limited passive range of motion. H...

Development and validation of a prognostic prediction model for lumbar-disc herniation based on machine learning and fusion of clinical text data and radiomic features.

OBJECTIVE: Based on preoperative clinical text data and lumbar magnetic resonance imaging (MRI), we applied machine learning (ML) algorithms to constr...

Novel Deep Learning Model to Estimate Knee Flexion and Adduction Moments with Wearable IMUs during Treadmill and Overground Walking.

A major issue after total knee replacement (TKR) surgery is asymmetric gait kinetics, which increases knee loads on the non-operated knee. This imbala...

Transforming surgical planning and procedures through the synergistic use of additive manufacturing, advanced materials and artificial intelligence: challenges and opportunities.

Additive manufacturing (AM) is a powerful approach in healthcare to augment the functionalities of patient-specific medical products and surgical tool...

Associations of CT Muscle Area and Density With Functional Outcomes and Mortality Across Anatomical Regions in Older Men.

BACKGROUND: The automated segmentation of computed tomography (CT) images has made their opportunistic use more feasible, yet, the association of musc...

Artificial Intelligence-Based prediction model for surgical site infection in metastatic spinal disease: a multicenter development and validation study.

BACKGROUND: Treatment of metastatic spinal disease often involves surgical intervention; however, surgical site infections (SSI) pose a great challeng...

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UNLABELLED: Early detection of glaucoma represents a vital factor in securing vision while the disease retains its position as one of the central caus...

Automation in tibial implant loosening detection using deep-learning segmentation.

PURPOSE: Patients with recurrent complaints after total knee arthroplasty may suffer from aseptic implant loosening. Current imaging modalities do not...

Mechanical properties of graphene oxide from machine-learning-driven simulations.

Graphene oxide (GO) materials have complex chemical structures that are linked to their macroscopic properties. Here we show that first-principles sim...

Predicting Retinal Nerve Fiber Layer Thickness From Ocular Hypertension Treatment Study Optic Disc Photographs.

IMPORTANCE: Deep learning predictions of retinal nerve fiber layer (RNFL) thickness derived from optic disc photographs may help to determine risk for...

Exploring the Development and Future Directions of Facial Bone Contouring: A Bibliometric and Visualization Analysis From 2005 to 2025.

The study aims to evaluate the global research landscape of facial bone contouring to identify current hotspots and future research directions. Data w...

Artificial Intelligence in Orthopedic Surgery: Current Applications, Challenges, and Future Directions.

Artificial intelligence (AI) drives transformative changes in orthopedic surgery, steering it toward precision and personalization through intelligent...

Pose estimation for pickleball players' kinematic analysis through MediaPipe-based deep learning: A pilot study.

Pickleball has gained popularity across diverse age groups. This sport has particular balls that require different hitting styles, like hitting dinks....