Orthopedics

Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis.

OBJECTIVES: Recent studies have shown that deep learning based on pre-treatment positron emission tomography (PET) or computed tomography (CT) is promising for distant metastasis (DM) and overall survival (OS) prognosis in head and neck cancer (HNC). However, lesion segmentation is typically required, resulting in a predictive power susceptible to variations in primary and lymph node gross tumor v...

Prediction of abrasive wears behavior of dental composites using an artificial neural network.

Resin composites are widely used as dental restorative materials since dental parts are subjected to prolonged wear and ultimately need to be replaced. The objective of this study is to analyze the potential of the feed-forward back propagation artificial neural network (ANN) in assessing the wear of dental composite materials when immersed in chewable tobacco solution, by utilizing the in-vitro t...

Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning.

Cardiovascular diseases (CVD) are the leading cause of death worldwide. People affected by CVDs may go undiagnosed until the occurrence of a serious h...

Recurrent neural networks as kinematics estimator and controller for redundant manipulators subject to physical constraints.

Redundant manipulators could be efficient tools in industrial production as a result of their dexterity. However, existing kinematic control methods f...

Force and Torque Characterization in the Actuation of a Walking-Assistance, Cable-Driven Exosuit.

Soft exosuits stand out when it comes to the development of walking-assistance devices thanks to both their higher degree of wearability, lower weight...

An Artificial Intelligence-Based Cosmesis Evaluation for Temporomandibular Joint Reconstruction.

OBJECTIVE: Management of the temporomandibular joint (TMJ) following condylar resection remains challenging in the field of mandibular reconstruction....

Modulations of one's sense of agency during human-machine interactions: A behavioural study using a full humanoid robot.

Although previous investigations reported a reduced sense of agency when individuals act with traditional machines, little is known about the mechanis...

Vertebrae Labeling via End-to-End Integral Regression Localization and Multi-Label Classification Network.

Accurate identification and localization of the vertebrae in CT scans is a critical and standard pre-processing step for clinical spinal diagnosis and...

Data-Driven Deep Supervision for Medical Image Segmentation.

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-dependent difficulties such as low image contrast, nois...

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning.

Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challe...

A Novel Method to Inspect 3D Ball Joint Socket Products Using 2D Convolutional Neural Network with Spatial and Channel Attention.

Product defect inspections are extremely important for industrial manufacturing processes. It is necessary to develop a special inspection system for ...

Deep Learning for Joint Pilot Design and Channel Estimation in MIMO-OFDM Systems.

In MIMO-OFDM systems, pilot design and estimation algorithm jointly determine the reliability and effectiveness of pilot-based channel estimation meth...

Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals.

Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by...

Can images crowdsourced from the internet be used to train generalizable joint dislocation deep learning algorithms?

OBJECTIVE: Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of t...

Study on the correlation between early three-dimensional gait analysis and clinical efficacy after robot-assisted total knee arthroplasty.

PURPOSE: Robot-assisted technology is a forefront of surgical innovation that improves the accuracy of total knee arthroplasty (TKA). But whether the ...

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Marrow Characterization From Whole-Body MRI: A Multicentric Feasibility Study.

OBJECTIVES: Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to ...

Deep Learning-Based Postoperative Recovery and Nursing of Total Hip Arthroplasty.

OBJECTIVE: To develop a deep learning-assisted recovery and nursing system after total hip arthroplasty and to conduct clinical trials in order to ver...

Design of Multimodal Neural Network Control System for Mechanically Driven Reconfigurable Robot.

According to the characteristics and division rules of the modules, this paper divides the rotary module, the swing module, and the mobile module. In ...

Detecting total hip arthroplasty dislocations using deep learning: clinical and Internet validation.

OBJECTIVE: Periprosthetic dislocations of total hip arthroplasty (THA) are time-sensitive injuries, as the longer diagnosis and treatment are delayed,...

Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.

BACKGROUND: Fragility hip fracture increases morbidity and mortality in older adult patients, especially within the first year. Identification of pati...