Orthopedics

Toward automatic C-arm positioning for standard projections in orthopedic surgery.

PURPOSE: Guidance and quality control in orthopedic surgery increasingly rely on intra-operative fluoroscopy using a mobile C-arm. The accurate acquisition of standardized and anatomy-specific projections is essential in this process. The corresponding iterative positioning of the C-arm is error prone and involves repeated manual acquisitions or even continuous fluoroscopy. To reduce time and radi...

Comparing the Bone Healing After Cold Ablation Robot-Guided Er:YAG Laser Osteotomy and Piezoelectric Osteotomy-A Pilot Study in a Minipig Mandible.

BACKGROUND AND OBJECTIVE: To take major advantage of erbium-doped yttrium aluminium garnet (Er:YAG) lasers in osteotomy-like freedom of cutting geometries and high accuracy-the integration and miniaturization of the robot, laser, and navigation technology was tried and applied to minipigs. The investigators hypothesized laser osteotomy would render acceptable bone healing based on the intraoperati...

Untethered-Bioinspired Quadrupedal Robot Based on Double-Chamber Pre-charged Pneumatic Soft Actuators with Highly Flexible Trunk.

Given that mobile soft robots are adaptable to the environment, they are always tethered with slow locomotion speed. Compared with other types of mobi...

The value of artificial neural networks for predicting length of stay, discharge disposition, and inpatient costs after anatomic and reverse shoulder arthroplasty.

HYPOTHESIS/PURPOSE: The objective is to develop and validate an artificial intelligence model, specifically an artificial neural network (ANN), to pre...

Integrative blockwise sparse analysis for tissue characterization and classification.

The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we devel...

Looking for Mimicry in a Snake Assemblage Using Deep Learning.

Batesian mimicry is a canonical example of evolution by natural selection, popularized by highly colorful species resembling unrelated models with ast...

Motion Sensors-Based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-Field Activities in Rugby Players.

Anterior cruciate ligament (ACL) injuries are common among athletes. Despite a successful return to sport (RTS) for most of the injured athletes, a si...

Artificial Intelligence-Assisted System in Postoperative Follow-up of Orthopedic Patients: Exploratory Quantitative and Qualitative Study.

BACKGROUND: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up...

Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment.

PURPOSE: The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to ...

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we develo...

WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images.

PURPOSE: The cup-to-disc ratio (CDR), a clinical metric of the relative size of the optic cup to the optic disc, is a key indicator of glaucoma, a chr...

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

This study reports the development of an artificial neural network computation model to predict the accumulation of crack density and crack length in ...

Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data.

Conventional inclusion criteria used in osteoarthritis clinical trials are not very effective in selecting patients who would benefit from a therapy b...

Osteoporotic hip fracture prediction from risk factors available in administrative claims data - A machine learning approach.

OBJECTIVE: Hip fractures are among the most frequently occurring fragility fractures in older adults, associated with a loss of quality of life, high ...

Is P&T Ready to Add Rapid Cycle Analytics to Formulary?

The intent of this article is to evaluate a novel approach, using rapid cycle analytics and real world evidence, to optimize and improve the medicati...

Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement.

The size of a device and its adaptability to human properties are important factors in developing a wearable device. In wearable robot research, there...

Assessment and prediction of spine surgery invasiveness with machine learning techniques.

BACKGROUND: The interest in Minimally Invasive Surgery (MIS) techniques has greatly increased in the recent years due to their significant advantages,...

Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.

: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retin...

Automated detection and classification of shoulder arthroplasty models using deep learning.

OBJECTIVE: To develop and evaluate the performance of deep convolutional neural networks (DCNN) to detect and identify specific total shoulder arthrop...

Deep Learning model for markerless tracking in spinal SBRT.

Stereotactic Body Radiation Therapy (SBRT), alternatively termed Stereotactic ABlative Radiotherapy (SABR) or Stereotactic RadioSurgery (SRS), deliver...