Orthopedics

Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis.

BACKGROUND: The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inte...

Use of Natural Language Processing Tools to Identify and Classify Periprosthetic Femur Fractures.

BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural language processing (NLP) tools are distinctive in their ability to extract critical information from unstructured text in the electronic health records. ...

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial.

BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improv...

Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.

This study's objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial inte...

Denoising of Scintillation Camera Images Using a Deep Convolutional Neural Network: A Monte Carlo Simulation Approach.

Scintillation camera images contain a large amount of Poisson noise. We have investigated whether noise can be removed in whole-body bone scans using ...

Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network.

Grading spondylolisthesis into several stages from MRI images is challenging because detecting critical vertebrae and locating landmarks in images of ...

Fully automated analysis for bone scintigraphy with artificial neural network: usefulness of bone scan index (BSI) in breast cancer.

OBJECTIVE: Artificial neural network (ANN) technology has been developed for clinical use to analyze bone scintigraphy with metastatic bone tumors. It...

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.

BACKGROUND: With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent...

Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers.

BACKGROUND: Super-resolution is an emerging method for enhancing MRI resolution; however, its impact on image quality is still unknown.

Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings.

Early diagnosis of sacroiliitis may lead to preventive treatment which can significantly improve the patient's quality of life in the long run. Oftent...

Machine and deep learning meet genome-scale metabolic modeling.

Omic data analysis is steadily growing as a driver of basic and applied molecular biology research. Core to the interpretation of complex and heteroge...

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

OBJECTIVE: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membra...

Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model.

Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires det...

On-field player workload exposure and knee injury risk monitoring via deep learning.

In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide an early warning system for athlete workload expo...

Metabolic cost adaptations during training with a soft exosuit assisting the hip joint.

Different adaptation rates have been reported in studies involving ankle exoskeletons designed to reduce the metabolic cost of their wearers. This wor...

Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.

OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic opt...

A feature agnostic approach for glaucoma detection in OCT volumes.

Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell w...

Transfusion after total knee arthroplasty can be predicted using the machine learning algorithm.

PURPOSE: A blood transfusion after total knee arthroplasty (TKA) is associated with an increase in complication and infection rates. However, no studi...

Screening and Assessment of Bone Health in Indian Women Using an Indigenous ELISA of Human Osteocalcin a Bone Turnover Marker.

Osteoporosis a major public health problem of the elderly, is associated with substantial morbidity and socio economic burden. The aim of the study wa...

A machine learning approach for predictive models of adverse events following spine surgery.

BACKGROUND: Rates of adverse events following spine surgery vary widely by patient-, diagnosis-, and procedure-related factors. It is critical to unde...