Orthopedics

Predictive validity of radiographic signs of complete discoid lateral meniscus in children using machine learning techniques.

The diagnostic utility of radiographic signs of complete discoid lateral meniscus remains controversial. This study aimed to investigate the diagnostic accuracy and determine which sign is most reliably detects the presence of a complete discoid lateral meniscus in children. A total of 141 knees (age 7-16) with complete discoid lateral meniscus and 141 age- and sex-matched knees with normal menisc...

How will digitalisation affect patient treatment in arthroplasty? Part I: Intraoperative aspects.

We cannot deny that technology has become an important part of our daily life, not only in automobiles, houses or cellphones but also in hospitals. In the OR, in particular for knee arthroplasty, image free navigation has proven to reduce the number of outliers and by that the revision rate in younger patients. Over the last years robotics has again been introduced into the operation theatres. How...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice...

Family history information extraction via deep joint learning.

Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family memb...

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.

Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. P...

Automated detection & classification of knee arthroplasty using deep learning.

BACKGROUND: Preoperative identification of knee arthroplasty is important for planning revision surgery. However, up to 10% of implants are not identi...

Prediction of Lower Limb Kinetics and Kinematics during Walking by a Single IMU on the Lower Back Using Machine Learning.

Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict gro...

Natural language processing for automated detection of incidental durotomy.

BACKGROUND: Incidental durotomy is a common intraoperative complication during spine surgery with potential implications for postoperative recovery, p...

New approach in the characterization of bioactive compounds isolated from Calycotome spinosa (L.) Link leaves by the use of negative electrospray ionization LITMS, LC-ESI-MS/MS, as well as NMR analysis.

Two novel compounds were isolated for the first time from Calycotome spinosa (L.) Link, an alkaloid 5-Hydroxy-1H-indole (4) and a cyclitol D-pinitol (...

Application of Machine Learning for Predicting Clinically Meaningful Outcome After Arthroscopic Femoroacetabular Impingement Surgery.

BACKGROUND: Hip arthroscopy has become an important tool for surgical treatment of intra-articular hip pathology. Predictive models for clinically mea...

Fully automatic estimation of pelvic sagittal inclination from anterior-posterior radiography image using deep learning framework.

BACKGROUND AND OBJECTIVE: Malposition of the acetabular component causes dislocation and prosthetic impingement after Total Hip Arthroplasty (THA), wh...

Bone age determination using only the index finger: a novel approach using a convolutional neural network compared with human radiologists.

BACKGROUND: Recently developed convolutional neural network (CNN) models determine bone age more accurately than radiologists.

Machine learning-based identification of hip arthroplasty designs.

BACKGROUND: The purposes of this study were to develop a machine learning-based implant recognition program and to verify its accuracy.

Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks.

The aim of this study is to use a multilayer perceptron (MLP) artificial neural network (ANN) for phaseless imaging the human heel (modeled as a bilay...

Feasibility of Single-Staged Bilateral Anterior Scoliosis Correction in Growing Patients.

STUDY DESIGN: Retrospective analysis.

Correlation of cancer antigen 15-3 (CA15-3) serum level and bony metastases in breast cancer patients.

Cancer antigen 15-3 (CA15-3) is a common tumor marker and the serum level of this tumor marker is evaluated during the treatment period (periodically...

Antioxidant capacity, antimicrobial activities and chemical composition of subsp essential oil.

This study aimed to evaluate the composition, antioxidant capacity and antibacterial effects of subsp. (baneh) essential oil on some important bacte...

Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.

PURPOSE: Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use m...

Non-Fusion Surgical Correction of Thoracic Idiopathic Scoliosis Using a Novel, Braided Vertebral Body Tethering Device: Minimum Follow-up of 4 Years.

UNLABELLED: Anterior vertebral body tethering to effect scoliosis correction in a growing spine has been shown to work with varying degrees of success...

Prediction of lower limb joint angles and moments during gait using artificial neural networks.

In recent years, gait analysis outside the laboratory attracts more and more attention in clinical applications as well as in life sciences. Wearable ...