Orthopedics

Estimation of lower limb joint moments using consumer realistic wearable sensor locations and deep learning - finding the balance between accuracy and consumer viability.

We used raw data from wearable sensors in consumer-realistic locations (replicating watch, arm phone strap, chest strap, etc.) to estimate lower-limb sagittal-plane joint moments during treadmill running and assessed the effect of a reduced number of sensor locations on estimation accuracy. Fifty mixed-ability runners (25 men and 25 women) ran on a treadmill at a range of speeds and gradients. The...

A multi-pseudo-sensor fusion approach to estimating the lower limb joint moments based on deep neural network.

Reliable feedback of gait variables, such as joint moments, is critical for designing controllers of intelligent assistive devices that can assist the wearer outdoors. To estimate lower extremity joint moments quickly and accurately outside the laboratory, a novel multimodal motion intent recognition system by fusing traditional deep learning models is proposed in this paper. The developed estimat...

Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos.

Concussions present a significant risk to athletes, with females exhibiting higher rates and prolonged recovery times than males. Current sideline con...

Applicability and performance of convolutional neural networks for the identification of periodontal bone loss in periapical radiographs: a scoping review.

The study aimed to review the applicability and performance of various Convolutional Neural Network (CNN) models for the identification of periodontal...

Uncalibrated Model-Free Visual Servo Control for Robotic Endoscopic with RCM Constraint Using Neural Networks.

With the advancement of robotic-assisted minimally invasive surgery, visual servo control has become a crucial technique for improving surgical outcom...

Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.

In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technology in total hip arthroplasty (THA), this study in...

Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to use multiple machine learning algorithms to explor...

Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images.

Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of disease. The greatest challenges today are the repetitiv...

Automated instance segmentation and registration of spinal vertebrae from CT-Scans with an improved 3D U-net neural network and corner point registration.

This paper presents a rapid and robust approach for 3D volumetric segmentation, labelling, and registration of human spinal vertebrae from CT scans us...

A Deep Learning Model for Comprehensive Automated Bone Lesion Detection and Classification on Staging Computed Tomography Scans.

RATIONALE AND OBJECTIVES: A common site of metastases for a variety of cancers is the bone, which is challenging and time consuming to review and impo...

Overcoming limitations to customize DeepVariant for domesticated animals with TrioTrain.

Generating high-quality variant callsets across diverse species remains challenging as most bioinformatic tools default to assumptions based on human ...

A Meta-Analysis of the Diagnosis of Condylar and Mandibular Fractures Based on 3-dimensional Imaging and Artificial Intelligence.

This article aims to review the literature, study the current situation of using 3D images and artificial intelligence-assisted methods to improve the...

Confidence-Driven Deep Learning Framework for Early Detection of Knee Osteoarthritis.

Knee Osteoarthritis (KOA) is a prevalent musculoskeletal disorder that severely impacts mobility and quality of life, particularly among older adults....

ssEM Image Restoration via Diffusion Models with Multi-output Joint Strategy for Noise Estimation.

Serial section electron microscopy (ssEM) is a pivotal technique for investigating neuronal connections and brain microstructures. However, imperfect ...

Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.

Robust differentiation between infarcted and normal myocardial tissue is essential for improving diagnostic accuracy and personalizing treatment in my...

AI-driven point cloud framework for predicting solder joint reliability using 3D FEA data.

Crack propagation in solder joints remains a major challenge impacting the thermo-mechanical reliability of electronic devices, underscoring the impor...

Mechanobiology-guided machine learning models for predicting long bone fracture healing across diverse scenarios.

BACKGROUND: Fracture healing is a complex, time-dependent process governed by biological and mechanical factors, including implant properties. While f...

Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases.

BACKGROUND AND PURPOSE:  Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patie...

External validation of a prediction model for disability and pain after lumbar disc herniation surgery: a prospective international registry-based cohort study.

BACKGROUND AND PURPOSE:  We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disabil...

Real-time super-resolution structured illumination microscopy: current progress in joint space and frequency reconstruction.

Due to its low light dose, ultra-high imaging speed and super-resolution, structured illumination microscopy (SIM) is now widely used in various appli...