Orthopedics

The artificial intelligence advantage: Supercharging exploratory data analysis.

Explorative data analysis (EDA) is a critical step in scientific projects, aiming to uncover valuable insights and patterns within data. Traditionally, EDA involves manual inspection, visualization, and various statistical methods. The advent of artificial intelligence (AI) and machine learning (ML) has the potential to improve EDA, offering more sophisticated approaches that enhance its efficacy....

Joint extraction of Chinese medical entities and relations based on RoBERTa and single-module global pointer.

BACKGROUND: Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompose the joint extraction task into multiple steps or multiple modules, resulting in local dependency in the meantime.

Image Quality Assessment of a Deep Learning-Based Automatic Bone Removal Algorithm for Cervical CTA.

BACKGROUND: The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the ...

Artificial intelligence in predicting postoperative heterotopic ossification following anterior cervical disc replacement.

OBJECTIVE: This study aimed to develop and validate a machine learning (ML) model to predict high-grade heterotopic ossification (HO) following Anteri...

Robotics and Artificial Intelligence in Minimally Invasive Spine Surgery: A Bibliometric and Visualization Analysis.

OBJECTIVE: This study aims to highlight the trends in the minimally invasive spine surgery (MISS) research field from the bibliometrics perspective.

Diagnosing the Severity of Knee Osteoarthritis Using Regression Scores From Artificial Intelligence Convolution Neural Networks.

BACKGROUND: This study focused on using deep learning neural networks to classify the severity of osteoarthritis in the knee. A continuous regression ...

AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs.

Despite well-defined criteria for radiographic diagnosis of atypical femur fractures (AFFs), missed and delayed diagnosis is common. An AFF diagnostic...

Precise Localization for Anatomo-Physiological Hallmarks of the Cervical Spine by Using Neural Memory Ordinary Differential Equation.

In the evaluation of cervical spine disorders, precise positioning of anatomo-physiological hallmarks is fundamental for calculating diverse measureme...

An artificial intelligence boost to MRI lumbar spine reporting.

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide vari...

A deep learning framework for the early detection of multi-retinal diseases.

Retinal images play a pivotal contribution to the diagnosis of various ocular conditions by ophthalmologists. Extensive research was conducted to enab...

Real-time prediction of postoperative spinal shape with machine learning models trained on finite element biomechanical simulations.

PURPOSE: Adolescent idiopathic scoliosis is a chronic disease that may require correction surgery. The finite element method (FEM) is a popular option...

Prediction of visual field progression with serial optic disc photographs using deep learning.

AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc...

Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty.

The size and axial alignment of prostheses, when planned during total knee replacement (TKA) are critical for recovery of knee function and improvemen...

Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures.

BACKGROUND: The frequency of hip and knee arthroplasty surgeries has been rising steadily in recent decades. This trend is attributed to an aging popu...

Risk prediction of kalaemia disturbance and acute kidney injury after total knee arthroplasty: use of a machine learning algorithm.

INTRODUCTION: Total knee arthroplasty (TKA) is a procedure associated with risks of electrolyte and kidney function disorders, which are rare but can ...

Deep learning classification of pediatric spinal radiographs for use in large scale imaging registries.

PURPOSE: The purpose of this study is to develop and apply an algorithm that automatically classifies spine radiographs of pediatric scoliosis patient...

Evaluating and Enhancing Large Language Models' Performance in Domain-Specific Medicine: Development and Usability Study With DocOA.

BACKGROUND: The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthriti...

Artificial intelligence in total and unicompartmental knee arthroplasty.

The application of Artificial intelligence (AI) and machine learning (ML) tools in total (TKA) and unicompartmental knee arthroplasty (UKA) emerges wi...

A systematic review of deep learning-based spinal bone lesion detection in medical images.

Spinal bone lesions encompass a wide array of pathologies, spanning from benign abnormalities to aggressive malignancies, such as diffusely localized ...