Orthopedics

Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.

BACKGROUND: Persistent critical illness (PerCI) is an immunosuppressive status. The underlying pathophysiology driving PerCI remains incompletely understood. The objectives of the study were to identify the biological signature of PerCI development, and to construct a reliable prediction model for patients who had suffered orthopedic trauma using machine learning techniques.

Efficacy and safety of robotic spine surgery: systematic review and meta-analysis.

BACKGROUND: Robotic surgery (RS) may offer benefits compared with freehand/conventional surgery (FS) in the treatment of patients with spinal disease. The aim of this study was to evaluate the efficacy and safety of RS versus FS in spinal fusion.

Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types.

Despite extensive efforts to generate and analyze reference genomes, genetic models to predict gene regulation and cell fate decisions are lacking for...

Deep residual neural-network-based robot joint fault diagnosis method.

A data driven method-based robot joint fault diagnosis method using deep residual neural network (DRNN) is proposed, where Resnet-based fault diagnosi...

Supervised machine learning and associated algorithms: applications in orthopedic surgery.

Supervised learning is the most common form of machine learning utilized in medical research. It is used to predict outcomes of interest or classify p...

Human-Robot Cooperative Strength Training Based on Robust Admittance Control Strategy.

A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. Stroke survivors can effectively train muscle streng...

Optimal planar leg geometry in robots and crabs for idealized rocky terrain.

Natural terrain is uneven so it may be beneficial to grasp onto the depressions or 'valleys' between obstacles when walking over such a surface. To ex...

Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm.

OBJECTIVES: To evaluate deep neural networks for automatic rib fracture detection on thoracic CT scans and to compare its performance with that of att...

A novel 3D lumbar vertebrae location and segmentation method based on the fusion envelope of 2D hybrid visual projection images.

In recent years, fast and precise lumbar vertebrae segmentation technology have been one of the important topics in practical medical diagnosis and as...

Biomechanical and Physiological Evaluation of Biologically-Inspired Hip Assistance With Belt-Type Soft Exosuits.

Hip-assisted soft exosuits have been reported for their effect on reducing the metabolic power of human walking. Currently, most studies focus on uni-...

Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears?

BACKGROUND/PURPOSE: The use of MRI as a diagnostic tool has gained popularity in the field of orthopedics. Although 3-dimensional (3D) MRI offers more...

A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.

BACKGROUND: Most of existing deep learning research in medical image analysis is focused on networks with stronger performance. These networks have ac...

An automatic extraction method on medical feature points based on PointNet++ for robot-assisted knee arthroplasty.

BACKGROUND: Image registration is a crucial technology in robot-assisted knee arthroplasty, which provides real-time patient information by registerin...

Evaluation of two semi-supervised learning methods and their combination for automatic classification of bone marrow cells.

Differential bone marrow (BM) cell counting is an important test for the diagnosis of various hematological diseases. However, it is difficult to accu...

Peripapillary atrophy classification using CNN deep learning for glaucoma screening.

Glaucoma is the second leading cause of blindness worldwide, and peripapillary atrophy (PPA) is a morphological symptom associated with it. Therefore,...

High-resolution knee plain radiography image synthesis using style generative adversarial network adaptive discriminator augmentation.

In this retrospective study, 10,000 anteroposterior (AP) radiography of the knee from a single institution was used to create medical data set that ar...

Deep-learning model associating lateral cervical radiographic features with Cormack-Lehane grade 3 or 4 glottic view.

Unanticipated difficult laryngoscopy is associated with serious airway-related complications. We aimed to develop and test a convolutional neural netw...

Development and model form assessment of an automatic subject-specific vertebra reconstruction method.

BACKGROUND: Current spine models for analog bench models, surgical navigation and training platforms are conventionally based on 3D models from anatom...

Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition.

Current state-of-the-art visual recognition systems usually rely on the following pipeline: 1) pretraining a neural network on a large-scale data set ...

A Classification Method for Thoracolumbar Vertebral Fractures due to Basketball Sports Injury Based on Deep Learning.

OBJECTIVE: There are more and more basketball competitions, to propose a classification method of thoracolumbar fractures to assist in the diagnosis o...