Orthopedics

Artificial Intelligence and its Applications in Orthodontics and Dentofacial Orthopedics.

In this article, the authors review the potential influence and benefits of artificial intelligence (AI) in orthodontics and dentofacial orthopedics with particular emphasis on current applications and emerging developments. Specific focus areas such as diagnosis, growth evaluation, treatment planning, personalized care, robotic technologies, virtual surgical planning, and improvements in clinical...

Osteoporosis prediction using lumbar CT Hounsfield units: comparative performance and clinical implications of seven machine learning models.

PURPOSE: This study aimed to evaluate the utility of L1-L4 average Hounsfield Unit (HU) values from lumbar spine computed tomography (CT) in predicting osteoporosis using multiple machine learning (ML) models. METHODS: We retrospectively analyzed 172 patients (≥ 50 years) who underwent lumbar spine surgery and received preoperative CT and dual-energy X-ray absorptiometry (DXA) within 3 months. Ost...

A New Insight into Imaging Diagnosis of Otosclerosis Enhanced by Machine Learning and Radiomics.

Otosclerosis is a disease affecting the middle and inner ear, characterized by abnormal bone remodeling that leads to stapes fixation and progressive ...

Artificial intelligence-driven 3D surface-topography app for screening and monitoring adolescent scoliosis: early results from a single institution.

PURPOSE: Radiation-free tools, such as scoliometers, ultrasound, and Moiré topography, have been explored for monitoring Adolescent Idiopathic Scolios...

Theory-Driven Experimental Discovery of M-N-C Electrocatalysts.

ConspectusAtomically dispersed M-N-C catalysts, owing to their high metal utilization and well-defined local structure, have been extensively applied ...

Interpretable prediction of prolonged length of stay for patients undergoing lumbar disc herniation surgery based on machine learning and SHAP.

Bone marrow proteomic profiling reveals TMEM109 as a biomarker for relapse in thrombotic thrombocytopenic purpura.

BACKGROUND: Thrombotic thrombocytopenic purpura (TTP) is a rare but life-threatening thrombotic microangiopathy, with a substantial risk of relapse de...

Artificial neural networks for predicting ground reaction forces, feet centers of pressure, spine loads, and trunk muscle forces during load-handling activities.

Excessive spinal loading is a key contributor to occupational musculoskeletal injuries. Numerous biomechanical models, ranging from simple to highly s...

Evaluating the methodological suitability of partial dependence plots and Shapley additive explanations for population-level interpretation of machine learning models in total joint arthroplasty.

BACKGROUND: Total joint arthroplasty (TJA) complications necessitate the development of accurate risk prediction models; however, interpretability in ...

Automated Abdominal Aortic Calcification Scores and Atherosclerotic Cardiovascular Disease in the UK Biobank Imaging Study.

BACKGROUND: Abdominal aortic calcification (AAC) is a subclinical measure of atherosclerotic cardiovascular disease (ASCVD). AAC can be captured on la...

Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study.

BACKGROUND: Rib fractures are present in 10%-15% of thoracic trauma cases but are often missed on chest radiographs, delaying diagnosis and treatment....

Deep Learning based Joint Geometry and Attribute Up-sampling for Large-Scale Colored Point Clouds.

Colored point cloud comprising geometry and attribute components is one of the mainstream representations enabling realistic and immersive 3D applicat...

Behavioral Cloning of Physiotherapists in Adapting Robot Control Parameter.

Robot-aided rehabilitation effectively supports treatment of upper-limb disorders and enhances outcomes when combined with traditional therapy. Artifi...

A tri-omics and machine learning framework identifies prognostic biomarkers and metabolic signatures in sepsis.

Sepsis is a complex systemic inflammatory syndrome that currently lacks stable and specific biomarkers. Multi-omics integration combined with machine ...

Clinically aligned whole-body MRI segmentation of skeletal metastases via Supervised Anatomical Pretraining.

In oncology practice, response assessment of metastatic disease requires reliable and reproducible quantification of measurable metastatic burden. Man...

Automated neural network femur segmentation performance in computed tomography images of older adults with obesity.

Femur segmentation is a precursor to image analysis pipelines that evaluate hip bone measures with subject-specific finite element models, but histori...

Evaluation of supervised machine learning models in predicting temporomandibular joint disc displacement on 3T magnetic resonance imaging.

OBJECTIVE: To evaluate supervised machine learning (ML) models for classifying temporomandibular joint (TMJ) disc displacement on MRI using morphometr...

From Joint Cognitive Systems to Human-AI Joint Cognitive Systems: A Theory Critique and Application to Obstetric Anesthesia Risk Assessment.

This article examines the joint cognitive systems framework as a foundation for understanding human-machine collaboration. Using Meleis's theory evalu...

Deciphering Multitarget Mechanisms of Phytochemical Flavonoids From Traditional Chinese Medicine: Emerging Insights Into Osteoporosis Therapeutics.

Osteoporosis is a common metabolic bone disorder characterized by reduced bone mass and compromised skeletal microstructure, increasing fracture risk....

Interpersonal Coordination Deficits in Joint Action in Pre-school Children With Autism Spectrum Disorder: Evidence From fNIRS Hyper-Scanning and Machine Learning.

PURPOSE: Whether children with autism spectrum disorder (ASD) exhibit interpersonal coordination deficits remains controversy. The study employed func...