Orthopedics

Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis.

: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-only models. However, previous studies have not statistically reported the additional effect of patient variables on the image-only models. This study aimed to statistically evaluate the osteoporosis identification ability of deep learning by combini...

Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT.

OBJECTIVE: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT.

MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning.

This paper proposes machine learning models for mapping surface electromyography (sEMG) signals to regression of joint angle, joint velocity, joint ac...

A siamese network with adaptive gated feature fusion for individual knee OA features grades prediction.

Grading individual knee osteoarthritis (OA) features is a fine-grained knee OA severity assessment. Existing methods ignore following problems: (1) mo...

ARMA-Based Segmentation of Human Limb Motion Sequences.

With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields...

Fully Soft Pressure Sensor Based on Bionic Spine-Pillar Structure for Robotics Motion Monitoring.

Soft and stretchable sensors are essential to the development of electronic skin, especially their potential applications in health care and intellige...

Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes.

Sarcopenia is associated with adverse clinical outcomes. CT-based skeletal muscle measurements for sarcopenia assessment are most commonly performed ...

Risk factors of osteoporosis in soldiers of the Armed Forces: A cross-sectional study from Western India.

BACKGROUND: Osteoporosis may result from risk factors such as smoking, alcohol, low body mass index, less physical exercise, and dietary calcium defic...

Prediction of hand-wrist maturation stages based on cervical vertebrae images using artificial intelligence.

OBJECTIVE: To predict the hand-wrist maturation stages based on the cervical vertebrae (CV) images, and to analyse the accuracy of the proposed algori...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-de...

Natural language processing for prediction of readmission in posterior lumbar fusion patients: which free-text notes have the most utility?

BACKGROUND CONTEXT: The increasing volume of free-text notes available in electronic health records has created an opportunity for natural language pr...

Deep learning approach to assess damage mechanics of bone tissue.

Machine learning methods have the potential to transform imaging techniques and analysis for healthcare applications with automation, making diagnosti...

Bioinspired High-Degrees of Freedom Soft Robotic Glove for Restoring Versatile and Comfortable Manipulation.

The human hand is one of the most complex and compact grippers that has arisen as a product of natural genetic engineering; it is highly versatile, as...

What can artificial intelligence and machine learning tell us? A review of applications to equine biomechanical research.

Artificial intelligence (AI) and machine learning (ML) are fascinating interdisciplinary scientific domains where machines are provided with an approx...

External Validation of Deep Learning Algorithm for Detecting and Visualizing Femoral Neck Fracture Including Displaced and Non-displaced Fracture on Plain X-ray.

This study aimed to develop a method for detection of femoral neck fracture (FNF) including displaced and non-displaced fractures using convolutional ...

A stochastic modeling approach for analyzing water resources systems.

Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the w...

Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer.

PURPOSE: We evaluated the performance of deep learning classifiers for bone scans of prostate cancer patients.

Deep learning-based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative.

Morphological changes in knee cartilage subregions are valuable imaging-based biomarkers for understanding progression of osteoarthritis, and they are...

Association of Machine Learning-Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis.

OBJECTIVE: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this stud...

Student Behavior Recognition System for the Classroom Environment Based on Skeleton Pose Estimation and Person Detection.

Human action recognition has attracted considerable research attention in the field of computer vision, especially for classroom environments. However...