Orthopedics

Predicting Corrosion Damage in the Human Body Using Artificial Intelligence: In Vitro Progress and Future Applications.

Artificial intelligence (AI) is used in the clinic to improve patient care. While the successes illustrate AI's impact, few studies have led to improved clinical outcomes. In this review, we focus on how AI models implemented in nonorthopedic fields of corrosion science may apply to the study of orthopedic alloys. We first define and introduce fundamental AI concepts and models, as well as physiol...

Deep learning in sex estimation from knee radiographs - A proof-of-concept study utilizing the Terry Anatomical Collection.

Although knee measurements yield high classification rates in metric sex estimation, there is a paucity of studies exploring the knee in artificial intelligence-based sexing. This proof-of-concept study aimed to develop deep learning algorithms for sex estimation from radiographs of reconstructed cadaver knee joints belonging to the Terry Anatomical Collection. A total of 199 knee radiographs were...

Cross-Domain Echocardiography Segmentation with Multi-Space Joint Adaptation.

The segmentation of the left ventricle endocardium (LV) and the left ventricle epicardium (LV) in echocardiography plays an important role in clinical...

Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis-Review of literature and in vitro case study.

The digital health industry is experiencing fast-paced research which can provide digital care programs and technologies to enhance the competence of ...

Robot-assisted versus navigated transpedicular spine fusion: A comparative study.

BACKGROUND: The aim of this study was to compare the intraoperative and postoperative outcomes between a robot-assisted versus a navigated transpedicu...

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.

The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal ...

Leveraging joint incremental learning objective with data ensemble for class incremental learning.

A class-incremental learning problem is characterized by training data becoming available in a phase-by-phase manner. Deep learning models suffer from...

Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existi...

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone...

Metamorphic aerial robot capable of mid-air shape morphing for rapid perching.

Aerial robots can perch onto structures at heights to reduce energy use or to remain firmly in place when interacting with their surroundings. Like ho...

Drone-assisted collection of environmental DNA from tree branches for biodiversity monitoring.

The protection and restoration of the biosphere is crucial for human resilience and well-being, but the scarcity of data on the status and distributio...

Prediction of Bone Healing around Dental Implants in Various Boundary Conditions by Deep Learning Network.

Tissue differentiation varies based on patients' conditions, such as occlusal force and bone properties. Thus, the design of the implants needs to tak...

Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI.

Background MRI is a powerful diagnostic tool with a long acquisition time. Recently, deep learning (DL) methods have provided accelerated high-quality...

Prediction of knee adduction moment using innovative instrumented insole and deep learning neural networks in healthy female individuals.

BACKGROUND: The knee adduction moment, a biomechanical risk factor of knee osteoarthritis, is typically measured in a gait laboratory with expensive e...

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care.

BACKGROUND:  With the rapid development of science and technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis of...

A multi-task convolutional neural network for classification and segmentation of chronic venous disorders.

Chronic Venous Disorders (CVD) of the lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North Americ...

Accuracy of Advanced Active Robot for Total Knee Arthroplasty: A Cadaveric Study.

Although the accuracy of other types of robotic systems for total knee arthroplasty (TKA) has been assessed in cadaveric studies, no investigations ha...

Software-related recalls in computer-assisted hip and knee arthroplasty.

PURPOSE: Computer-assisted arthroplasty supports the surgeons in planning, simulating, and performing the replacement procedure, using robotic or navi...

Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation.

BACKGROUND: Osteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-lear...

Ethical issues of the use of AI-driven mobile apps for education.

Nowadays, artificial intelligence (AI) affects our lives every single day and brings with it both benefits and risks for all spheres of human activiti...