Orthopedics

Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model.

Prestressed girders reduce cracking and allow for long spans, but their construction requires complex equipment and strict quality control. Their accurate design depends on a precise knowledge of tensioning force and stresses, as well as monitoring the tendon force to prevent excessive creep. Estimating tendon stress is challenging due to limited access to prestressing tendons. This study utilizes...

Reconstructive Allograft Preparation for Long Bone Intercalary Segments After Tumor Resections: Toronto Sarcoma Protocol.

BACKGROUND: The Reconstructive Allograft Preparation by Toronto Sarcoma (RAPTORS) protocol is reliable and reproducible without substantially adding to the surgical reconstruction time or cost. Our technique includes clearance of debris, lavage of the medullary canal, pressurized filling of the medullary canal with antibiotic-laden cement for its mechanical and antimicrobial properties, and insert...

Harvest and Application of Bone Marrow Aspirate Concentrate to Address Acetabular Chondral Damage During Hip Arthroscopy.

BACKGROUND: During hip arthroscopy, managing concomitant cartilage damage and chondrolabral junction breakdown remains an ongoing challenge for orthop...

Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk s...

A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study.

BACKGROUND: The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better m...

Automatic multi-label temporal bone computed tomography segmentation with deep learning.

BACKGROUND: Manually segmenting temporal bone computed tomography (CT) images is difficult. Despite accurate automatic segmentation in previous studie...

Comparison of evaluation metrics of deep learning for imbalanced imaging data in osteoarthritis studies.

PURPOSE: To compare the evaluation metrics for deep learning methods that were developed using imbalanced imaging data in osteoarthritis studies.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.

PURPOSE: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of...

Sequence based local-global information fusion framework for vertebrae detection under pathological and FOV variation challenges.

Automated vertebrae detection (identification and localization) aims to identify vertebrae and locate their centroids in medical images, which is a cr...

Combining deep learning and machine learning for the automatic identification of hip prosthesis failure: Development, validation and explainability analysis.

AIM: Revision hip arthroplasty has a less favorable outcome than primary total hip arthroplasty and an understanding of the timing of total hip arthro...

Development of a deep learning system to detect glaucoma using macular vertical optical coherence tomography scans of myopic eyes.

Myopia is one of the risk factors for glaucoma, making accurate diagnosis of glaucoma in myopic eyes particularly important. However, diagnosis of gla...

Weight-shifting-based robot control system improves the weight-bearing rate and balance ability of the static standing position in hip osteoarthritis patients: a randomized controlled trial focusing on outcomes after total hip arthroplasty.

BACKGROUND: After a total hip arthroplasty (THA), standing and walking balance are greatly affected in the early stages of recovery, so it is importan...

Deep learning for detection and 3D segmentation of maxillofacial bone lesions in cone beam CT.

OBJECTIVES: To develop an automated deep-learning algorithm for detection and 3D segmentation of incidental bone lesions in maxillofacial CBCT scans.

Development of deep learning model and evaluation in real clinical practice of lingual mandibular bone depression (Stafne cyst) on panoramic radiographs.

OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any s...

Comparison of short-term clinical outcomes between robot-assisted and freehand pedicle screw placement in spine surgery: a meta-analysis and systematic review.

STUDY DESIGN: Meta-analysis and systematic review.

A Joint Extraction System Based on Conditional Layer Normalization for Health Monitoring.

Natural language processing (NLP) technology has played a pivotal role in health monitoring as an important artificial intelligence method. As a key t...

Exposure to Extended Reality and Artificial Intelligence-Based Manifestations: A Primer on the Future of Hip and Knee Arthroplasty.

BACKGROUND: Software-infused services, from robot-assisted and wearable technologies to artificial intelligence (AI)-laden analytics, continue to augm...

Random forest identifies predictors of discharge destination following total shoulder arthroplasty.

BACKGROUND: Machine learning algorithms are finding increasing use in prediction of surgical outcomes in orthopedics. Random forest is one of such alg...

Robot-assisted ultrasound reconstruction for spine surgery: from bench-top to pre-clinical study.

PURPOSE: Robot-assisted ultrasound (rUS) systems have already been used to provide non-radiative three-dimensional (3D) reconstructions that form the ...

Robotic solution for orthopedic surgery.