Orthopedics

A New Strategy for Disc Cutter Wear Status Perception Using Vibration Detection and Machine Learning.

Carrying out status monitoring and fault-diagnosis research on cutter-wear status is of great significance for real-time understanding of the health status of Tunnel Boring Machine (TBM) equipment and reducing downtime losses. In this work, we proposed a new method to diagnose the abnormal wear state of the disc cutter by using brain-like artificial intelligence to process and analyze the vibratio...

Effect of button layout on the exploration and learning of robot operation using an unfamiliar controller.

Robots are becoming increasingly accessible to both experts and non-experts. Therefore, establishing a method for learning robot operations that can be easily mastered by non-experts is important. With this in mind, we aimed to develop a method that facilitates skill acquisition for non-experts that operate robots. As a first step, this study examined the effects of button layout on the exploratio...

Detection Method of Athlete Joint Injury Based on Deep Learning Model.

The research on accurate and intelligent segmentation of knee joint MRI images is of great significance to reduce the work intensity of clinical docto...

Radiomics and Deep Learning for Disease Detection in Musculoskeletal Radiology: An Overview of Novel MRI- and CT-Based Approaches.

Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radio...

Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events.

CT-based body composition (BC) measurements have historically been too resource intensive to analyze for widespread use and have lacked robust compar...

Joint Label Inference and Discriminant Embedding.

Graph-based learning in semisupervised models provides an effective tool for modeling big data sets in high-dimensional spaces. It has been useful for...

Sex Imbalance Produces Biased Deep Learning Models for Knee Osteoarthritis Detection.

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has b...

Automated Protocoling for MRI Exams-Challenges and Solutions.

Automated protocoling for MRI examinations is an amendable target for workflow automation with artificial intelligence. However, there are still chall...

Classifying Temporomandibular Disorder with Artificial Intelligent Architecture Using Magnetic Resonance Imaging.

This study proposes a new diagnostic tool for automatically extracting discriminative features and detecting temporomandibular joint disc displacement...

Synthetic CT in Musculoskeletal Disorders: A Systematic Review.

Repeated computed tomography (CT) examinations increase patients' ionizing radiation exposure and health costs, making an alternative method desirable...

A Joint Automatic Modulation Classification Scheme in Spatial Cognitive Communication.

Automatic modulation discrimination (AMC) is one of the critical technologies in spatial cognitive communication systems. Building a high-performance ...

Biomedical Diagnosis of Leukemia Using a Deep Learner Classifier.

Leukemia cancer is the most common type of cancer that occurs in childhood. The most common types are acute lymphocytic leukemia (ALL) and acute myelo...

Adaptive Biological Neural Network Control and Virtual Realization for Engineering Manipulator.

By analyzing the feasibility of the digital twin technology in the assembly of construction machinery, the assembly process of the construction manipu...

Answer to the letter to the editor by Zhi-Hui Dai concerning "Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion" by Rudisill SS et al. (Eur Spine J [2022]; doi: 10.1007/s00586-022-07238-3).

Improvement of Patient Classification Using Feature Selection Applied to Bidirectional Axial Transmission.

Osteoporosis is still a worldwide problem, particularly due to associated fragility fractures. Patients at risk of fracture are currently detected usi...

Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.

PURPOSE: Evaluating lower extremity alignment using full-leg plain radiographs is an essential step in diagnosis and treatment of patients with knee o...

Deep learning method for reducing metal artifacts in dental cone-beam CT using supplementary information from intra-oral scan.

Recently, dental cone-beam computed tomography (CBCT) methods have been improved to significantly reduce radiation dose while maintaining image resolu...

An automated deep learning method and novel cardiac index to detect canine cardiomegaly from simple radiography.

Since most of degenerative canine heart diseases accompany cardiomegaly, early detection of cardiac enlargement is main priority healthcare issue for ...

Regional Language Speech Recognition from Bone-Conducted Speech Signals through Different Deep Learning Architectures.

Bone-conducted microphone (BCM) senses vibrations from bones in the skull during speech to electrical audio signal. When transmitting speech signals, ...