Orthopedics

FIRST-ICU: forecasting interventions and risk stratification in the ICU using graph neural network autoencoders.

Critically ill patients frequently require multiple concurrent interventions with complex interdependencies, yet existing prediction models treat these as independent events. We developed FIRST-ICU (Forecasting Interventions and Risk Stratification in the ICU), a unified deep learning framework integrating a graph neural network encoder, LSTM, and a novel Intervention Interaction Attention Module ...

Tribological performance of Al5052/B₄C/Granite hybrid composites: machine learning prediction and multi-response optimization.

This study investigates the sustainable wear performance of Al5052/B₄C/granite hybrid composites produced by the stir casting process. Wear tests were executed on a pin on disc by varying load from 20 N to 50 N and sliding speed from 2 m/s to 3 m/s to evaluate the specific wear rate (SWR) and coefficient of friction (COF). From the results, the lowest specific wear rate of 0.201 × 10⁻³ mm³/Nm was ...

Cartilage Injury: Update on Diagnosis and Image-guided Therapy.

Cartilage injury is a prevalent source of pain and disability, often progressing to osteoarthritis if untreated. MR imaging represents the reference s...

Yolov7 neural network for pelvic X-rays after total hip arthroplasty: automatically measuring component position parameters- a retrospective feasibility study.

BACKGROUND: After total hip arthroplasty (THA), regular follow-up X-rays are required to evaluate the position of the prosthesis. However, measuring t...

Predicting kinesiophobia in knee osteoarthritis: a head-to-head comparison between machine learning and traditional regression models.

BACKGROUND: Although machine learning (ML) holds promise for improving clinical identification, its application to kinesiophobia in knee osteoarthriti...

Extracranial vascular association of moyamoya disease: a systematic review and machine learning analysis.

BACKGROUND: Intracranial steno-occlusive lesions are characteristic of moyamoya disease (MMD), but increasing reports of extracranial vascular involve...

An expert-led benchmark using common patient questions: evaluating large language models for adolescent idiopathic scoliosis education.

AIM/BACKGROUND: Large language models (LLMs) are increasingly used by patients to obtain medical information. Adolescent idiopathic scoliosis (AIS), a...

Predictive Model for Bone Availability in Patients With Unilateral Cleft Lip and Palate: A Machine Learning Approach.

ObjectiveTo develop a predictive model for estimating cortical bone thickness at any maxillary location in patients with unilateral cleft lip and pala...

External validation of machine learning models for estimation of mortality 1, 3, 6, and 12 months after hip fracture on 5,055 consecutive patients.

BACKGROUND AND PURPOSE:  Many models for prediction of mortality after hip fracture have been published but few have undergone external validation, us...

Machine learning-based clinical tool for identifying factors associated with symptomatic knee osteoarthritis: the Nagahama study.

BACKGROUND: A clinical tool that evaluates factors associated with symptomatic knee osteoarthritis (OA) based on modifiable factors is lacking. This s...

Integrating network toxicology, molecular docking and experimental validation reveals potential mechanisms of DEHP in osteoarthritis.

Di(2-ethylhexyl) phthalate (DEHP), a ubiquitous environmental endocrine disruptor, has been implicated in osteoarthritis (OA) pathogenesis, although t...

Hybrid vision transformer and ensemble machine learning framework for automated atherosclerotic plaque classification in intravascular ultrasound imaging.

Atherosclerotic plaque classification in intravascular ultrasound (IVUS) imaging is crucial for cardiovascular disease diagnosis and treatment plannin...

AI-assisted extraction of opportunistic findings from oncologic CT reports using large language models.

Opportunistic findings at imaging (iOFs), such as osteoporosis, liver steatosis, or coronary artery calcifications, are clinically relevant abnormalit...

LLMs as emerging tools for understanding and managing bone metastasis and cancer-induced bone pain.

Artificial intelligence (AI) chatbots powered by large language models (LLMs) show promise in human-like responses, yet their utility for complex biom...

Assessment of OpenEvidence Responses to American Academy of Orthopaedic Surgeons Clinical Practice Guidelines for Anterior Cruciate Ligament Reconstruction.

INTRODUCTION/OBJECTIVES: General-purpose large language models (LLMs) have substantial limitations, including fabricated references and inconsistent c...

AI and knowledge driven computation of rock mass characteristic parameters across engineering projects.

With the continuous development of underground construction, represented by transportation tunnels, municipal utility tunnels and hydraulic tunnels, a...

Identification of Chronic Stress-Related Biomarkers for Potential Diagnosis and Treatment of Osteoporosis: An Integrated Multi-omic and Clinical Data Analysis.

OBJECTIVE: The mechanisms through which chronic stress-related genes influence the diagnosis of osteoporosis (OP), where chronic stress serves as a ri...

Identification of aging-related signature genes in temporomandibular joint degeneration based on bioinformatics.

BACKGROUND: Degenerative temporomandibular joint diseases (TMJ-DJD) are increasingly affecting elderly populations, with aging being a significant ris...

Automatic detection of panoramic positioning errors and development of an objective image quality scoring system using deep learning.

OBJECTIVES: To develop a deep learning model capable of automatically detecting common positioning errors in panoramic radiographs and to establish an...

MedADL: High-Throughput Information Extraction of Functional Status from Electronic Health Records to Advance Frailty Assessment in Older Adults.

BACKGROUND: Functional status is essential for assessing frailty and planning care in older adults but is often under-documented in the structured fie...