Orthopedics

A Wearable Motion Capture Dataset for Gait Analysis Using IMUs and Shank-Mounted Egocentric Cameras.

Walking kinematics offer critical insights into human gait, enabling clinicians to assess motor function, diagnose impairments, and monitor rehabilitation progress. With the rise of machine learning, wearable sensors are increasingly used to estimate joint kinematics. To advance these fields, we introduce a dataset comprising 14 walking trials performed by 10 healthy participants across various sp...

A zero-watermark scheme for the protection of pediatric orthopedic medical images using dual-source collaborative cross-attention mechanism.

Digital medical images of pediatric orthopedic diseases are widely exchanged and transmitted on medical sharing platforms for medical usage. However, it faces serious copyright challenges due to the ease of replication and the limited effectiveness of copyright protection tools. To solve the problems, this paper pro- poses a deep learning zero-watermark scheme based on a dual-source collaborative ...

BoneCoT: multicentre validation of a whole-body skeleton foundation model for bone metastases guided by clinician-derived chain of thought.

Given the rising incidence of bone metastases, computed tomography is widely used worldwide as the initial imaging modality for their detection. Accur...

Multidirectional Optical Bone Densitometry Using a Simulation-Based Machine Learning Model: Experimental Validation with Bone Phantoms.

PURPOSE: While the multidirectional optical bone densitometry approach, originally proposed based on simulation, has been previously reported, its exp...

An adaptive attention U-network for recognizing ultrasound images.

ObjectiveThe traditional method of intraspinal anesthesia relies on surface anatomical landmarks for positioning, which is associated with a low accur...

Toward autonomous robotic-assisted and microrobotic surgery.

Autonomous robotic-assisted surgery (RAS) has emerged as a promising objective in biomedical technology, further enhanced by miniaturization toward mi...

User Acceptance of an AI-Powered Medical History-Taking Training System Among Undergraduate Medical Students: Mixed Methods Study.

BACKGROUND: Artificial intelligence (AI)-powered virtual patient systems provide medical students with repeatable practice environments for history-ta...

An explainable machine learning model for predicting one-year osteoporosis risk: development and validation in a prospective cohort.

OBJECTIVE: This study aimed to develop and validate an interpretable machine learning model using readily available biochemical indicators to predict ...

Identification and Experimental Verification of Key Genes Related to the Ras Signaling Pathway and the Hippo Signaling Pathway in Osteoarthritis Based on Transcriptome Data.

BACKGROUND: Osteoarthritis (OA) is a chronic degenerative joint disease characterized by the progressive deterioration of articular cartilage, signifi...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

Development and Validation of Machine Learning Models to Optimize Imaging and Referrals for Dizziness in the Emergency Department.

BACKGROUND: Dizziness and vertigo are common emergency department (ED) presentations, but only 2%-5% receive a serious diagnosis, such as stroke or tr...

Post-stroke rehabilitation in inflammatory rheumatic diseases: outcome measures, digital tools, and patient education perspectives.

Inflammatory rheumatic diseases (IRDs) represent a significant risk factor for cerebrovascular events, independent of traditional cardiovascular risk ...

Early prediction of joint space narrowing in rheumatoid arthritis using AI-quantified bilateral joint space asymmetry on hand radiography.

PURPOSE: Joint space narrowing (JSN) in rheumatoid arthritis (RA) can progress even during clinical remission. Conventional imaging lacks sensitivity ...

EMG-Based Gait Estimation Using Koopman-Inspired Method.

EMG-based state estimation and prediction in human-machine interaction,biomechanics, and robotics applications is an emerging approach offering potent...

Multi-view constrained semi-supervised vertebra detection for 3D ultrasound spine volume.

BACKGROUND: Scoliosis is a spinal disorder characterized by a three-dimensional (3D) deformity of the vertebral column. 3D ultrasound imaging has been...

BHOD: a bone health optimized dietary pattern designed for osteoporosis prevention.

Existing dietary patterns were not specifically designed to target osteoporosis and lack the precision required for effective prevention. We aimed to ...

Application of a deep learning method based on CBCT panoramic reconstruction images for differentiating operationally defined cystic and neoplastic jaw lesions from osteomyelitis: a single-center retrospective study.

This single-center retrospective study developed and internally validated a two-dimensional deep learning model based on cone-beam computed tomography...

Artificial intelligence for scoliosis surgical planning and postoperative prediction.

Adolescent idiopathic scoliosis (AIS) surgery requires precise fusion segment selection and reliable prediction of postoperative alignment, yet curren...

Automatic lesion segmentation in ⁶⁸Ga-PSMA PET/CT and ¹⁷⁷Lu-PSMA SPECT/CT: added value of PET-guided SPECT in a bicentric study.

BACKGROUND: Manual segmentation of prostate cancer metastases on PSMA PET/CT and SPECT/CT is time-consuming and poorly scalable, particularly in highl...

Joint-Shrinkage Pattern Matching for Small-Sample and Imbalanced ERP Decoding in Brain-Computer Interfaces.

Event-related potential (ERP)-based brain-computer interface (BCI) systems are approaching sub-microvolt-level resolution, enabling detailed decoding ...