Orthopedics

Estimating proton density fat fraction using computed tomography attenuation in skeletal muscle and adipose tissue in a prospective clinical cohort.

BACKGROUND: Proton density fat fraction (PDFF) measured using magnetic resonance imaging (MRI) is considered a noninvasive reference measure of fat deposition in various tissues and has been proposed as a quantitative indicator of tissue quality. Although the contraindications of MRI limit PDFF as a routine clinical tool, computed tomography (CT) scans are often available clinically. Currently, th...

Model utility and explainability in federated learning - A case study in healthcare using fundus oculi datasets.

OBJECTIVE: Introduce a case study for Federated Learning (FL) in healthcare, addressing challenges posed by patient privacy and limited large-scale datasets. Our goal is to assess the features learned by FL methods in a simulated, diverse setting that emphasizes realistic data heterogeneity, and to analyze the learned representations for their medical relevance using both local and global explaina...

Deviation From AI-Predicted Implant Sizes in Total Hip Arthroplasty Is Associated With Increased Complication Risk.

BACKGROUND: Patient characteristics may predict implant sizes in total hip arthroplasty (THA), but the clinical value and generalizability of such mod...

Machine learning applications for anterior cruciate ligament injury prediction and rehabilitation in sports: A scoping review with evidence synthesis.

PURPOSE: To map and synthesise current evidence on machine learning (ML) applications for anterior cruciate ligament (ACL) injury risk estimation, reh...

Multimodal Deep Learning-Based Screening of Degenerative Temporomandibular Joint Disease Using 2D Radiography: A Cost-Effective and Low-Radiation Approach.

OBJECTIVES: This study aimed to develop and preliminarily validate a multimodal deep learning model based on two-dimensional maxillofacial imaging for...

The application of machine learning-assisted serum SERS technology in the early screening and prognosis evaluation of osteoporosis.

Early detection, early intervention, early treatment, and timely prognostic monitoring of osteoporosis are crucial for improving patients' quality of ...

Evaluating Generative Artificial Intelligence Models' Responses to Questions About Scaphoid Fracture and Scaphoid Nonunion.

PURPOSE: To evaluate and compare the responses of ChatGPT and Google Gemini to common patient questions about scaphoid fracture and scaphoid nonunion,...

Automated Segmentation of Augmented Bone After Transalveolar Sinus Floor Elevation Using Deep Learning.

This study aimed to evaluate the performance of deep learning models for segmenting the augmented bone following transalveolar sinus floor elevation (...

[Deep learning-based assessment of periodontal ligament area changes in maxillary central incisors under different orthodontic regimens using cone-beam CT images].

Objective: To investigate the differences in the changes of periodontal ligament area (PDLA) and related clinical indicators before and after maxillar...

Rejoining fragmented ancient bamboo slips with physics-driven deep learning.

Bamboo slips are a crucial medium for recording ancient civilizations in East Asia. However, many excavated bamboo slips have been fragmented into tho...

An Automated Framework for Mandibular Reconstruction: Evaluation and Clinical Application.

BACKGROUND: Mandibular reconstruction suffers from limitations in automation and objectivity. This study aimed to develop an automated framework to ad...

The feasibility of using deep learning technologies to preliminarily identify patients with advanced knee osteoarthritis via smartphone videos.

Targeting the osteoporotic bone microenvironment: Mechanistic insight and therapeutic biomaterials for accelerating bone regeneration.

Osteoporotic bone defects (OBD) present a major clinical challenge, largely due to a pathological bone microenvironment that severely compromises rege...

Do ChatGPT and Gemini provide accurate answers to patient questions about glenohumeral arthritis?

BACKGROUND: Machine learning, a subset of artificial intelligence, enables large language models (LLMs) like ChatGPT and Gemini to analyze data, learn...

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study.

BACKGROUND: Chronic back pain is a severe health condition with underlying biopsychosocial factors that make diagnosis difficult, and pain chronicity ...

Identifying patients at risk for short-term adverse events after hip arthroscopy: a machine learning analysis of a national database.

PURPOSE: To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight ...

An algorithm for automated femoral leg length and offset calculations on pelvis radiographs.

INTRODUCTION: Manual measurement of leg length (LL) and offset can be tedious. This study developed an automated algorithm for measuring LL and offset...

Machine learning model integrating oral microbiota and clinical features for predicting osteoporosis and bone loss in high-altitude populations.

A Biologically Lubricating Allicin-Based Nanoplatform for Remodeling the Inflammation-Senescence Axis in the Treatment of Periodontitis.

Periodontitis is driven by a self-reinforcing cycle of persistent inflammation and cellular senescence, further exacerbated by pathogenic microbial co...

A machine learning-assisted Ag-TiO2 SERS platform for intraoperative osteomyelitis diagnosis.

Osteomyelitis is a progressive bone infection with high disability and recurrence rates. However, current diagnostic approaches, including bacterial c...