Orthopedics

Use of Artificial Intelligence in Cobb Angle Measurement for Scoliosis: Retrospective Reliability and Accuracy Study of a Mobile App.

BACKGROUND: Scoliosis is a spinal deformity in which one or more spinal segments bend to the side or show vertebral rotation. Some artificial intelligence (AI) apps have already been developed for measuring the Cobb angle in patients with scoliosis. These apps still require doctors to perform certain measurements, which can lead to interobserver variability. The AI app (cobbAngle pro) in this stud...

ACL-DUNet: A tumor segmentation method based on multiple attention and densely connected breast ultrasound images.

Breast cancer is the most common cancer in women. Breast masses are one of the distinctive signs for diagnosing breast cancer, and ultrasound is widely used for screening as a non-invasive and effective method for breast examination. In this study, we used the Mendeley and BUSI datasets, comprising 250 images (100 benign, 150 malignant) and 780 images (133 normal, 487 benign, 210 malignant), respe...

Optimization of grinding parameters in robotic-assisted preparation of cracked teeth based on fracture mechanics: FEA and experiment.

BACKGROUND AND OBJECTIVES: If left untreated, cracked teeth can lead to tooth loss, of which the incidence is 70%. Dental preparation is an effective ...

Assessment of Artificial Intelligence Chatbot Responses to Common Patient Questions on Bone Sarcoma.

BACKGROUND AND OBJECTIVES: The potential impacts of artificial intelligence (AI) chatbots on care for patients with bone sarcoma is poorly understood....

SPINEPS-automatic whole spine segmentation of T2-weighted MR images using a two-phase approach to multi-class semantic and instance segmentation.

OBJECTIVES: Introducing SPINEPS, a deep learning method for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, in...

Utilization of Machine Learning Models to More Accurately Predict Case Duration in Primary Total Joint Arthroplasty.

BACKGROUND: Accurate operative scheduling is essential for the appropriation of operating room esources. We sought to implement a machine learning mod...

Temporomandibular joint CBCT image segmentation via multi-view ensemble learning network.

Accurate segmentation of the temporomandibular joint (TMJ) from cone beam CT (CBCT) images holds significant clinical value for diagnosing temporomand...

Trends in the prevalence of osteoporosis and effects of heavy metal exposure using interpretable machine learning.

There is limited evidence that heavy metals exposure contributes to osteoporosis. Multi-parameter scoring machine learning (ML) techniques were develo...

Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. The clinical importance of BAE is in understanding t...

Evaluation of a novel robotic testing method for stability and kinematics of total knee arthroplasty.

PURPOSE: This work developed a novel preclinical test of total knee replacements (TKRs) in order to explain TKR instability linked to patient dissatis...

An explainable machine learning estimated biological age based on morphological parameters of the spine.

Accurately estimating biological age is beneficial for measuring aging and predicting risk. It is widely accepted that the prevalence of spine compres...

Knee Osteoarthritis SCAENet: Adaptive Knee Osteoarthritis Severity Assessment Using Spatial Separable Convolution with Attention-Based Ensemble Networks with Hybrid Optimization Strategy.

Osteoarthritis (OA) of the knee is a chronic state that significantly lowers the quality of life for its patients. Early detection and lifetime monito...

Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty.

BACKGROUND: While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated i...

AI in radiology: From promise to practice - A guide to effective integration.

While Artificial Intelligence (AI) has the potential to transform the field of diagnostic radiology, important obstacles still inhibit its integration...

as a Novel Biomarker for Colon Cancer Bone Metastasis with Machine Learning and Immunohistochemistry Validation.

Bone metastasis (BM) is a serious clinical symptom of advanced colorectal cancer. However, there is a lack of effective biomarkers for early diagnosi...

Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans to diagnose bone cancer. Manual methods are labor-...

OrthoMortPred: Predicting one-year mortality following orthopedic hospitalization.

OBJECTIVE: Predicting mortality risk following orthopedic surgery is crucial for informed decision-making and patient care. This study aims to develop...

"Dictionary of immune responses" reveals the critical role of monocytes and the core target IRF7 in intervertebral disc degeneration.

BACKGROUND: Intervertebral disc degeneration (IDD) is widely regarded as the primary contributor to low back pain(LBP). As an immune-privileged organ,...

Can ChatGPT reliably answer the most common patient questions regarding total shoulder arthroplasty?

BACKGROUND: Increasingly, patients are turning to artificial intelligence (AI) programs such as ChatGPT to answer medical questions either before or a...

A Biomimetic Adhesive Disc for Robotic Adhesion Sliding Inspired by the Net-Winged Midge Larva.

Net-winged midge larvae (Blephariceridae) are known for their remarkable ability to adhere to and crawl on the slippery surfaces of rocks in fast-flow...