Orthopedics

Radiation dose reduction and image quality improvement with ultra-high resolution temporal bone CT using deep learning-based reconstruction: An anatomical study.

PURPOSE: The purpose of this study was to evaluate the achievable radiation dose reduction of an ultra-high resolution computed tomography (UHR-CT) scanner using deep learning reconstruction (DLR) while maintaining temporal bone image quality equal to or better than high-resolution CT (HR-CT).

Automatic detection of midfacial fractures in facial bone CT images using deep learning-based object detection models.

BACKGROUND: Midfacial fractures are among the most frequent facial fractures. Surgery is recommended within 2 weeks of injury, but this time frame is often extended because the fracture is missed on diagnostic imaging in the busy emergency medicine setting. Using deep learning technology, which has progressed markedly in various fields, we attempted to develop a system for the automatic detection ...

Application of ChatGPT for Orthopedic Surgeries and Patient Care.

Artificial intelligence (AI) has rapidly transformed various aspects of life, and the launch of the chatbot "ChatGPT" by OpenAI in November 2022 has g...

Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.

Radiation treatment of cancers like prostate or cervix cancer requires considering nearby bone structures like vertebrae. In this work, we present and...

D-TrAttUnet: Toward hybrid CNN-transformer architecture for generic and subtle segmentation in medical images.

Over the past two decades, machine analysis of medical imaging has advanced rapidly, opening up significant potential for several important medical ap...

Machine learning-based bioimpedance assessment of knee osteoarthritis severity.

This study proposes a multiclass model to classify the severity of knee osteoarthritis (KOA) using bioimpedance measurements. The experimental setup c...

Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.

BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmissions following total joint replacement surgeries...

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compres...

A reliable deep-learning-based method for alveolar bone quantification using a murine model of periodontitis and micro-computed tomography imaging.

OBJECTIVES: This study focuses on artificial intelligence (AI)-assisted analysis of alveolar bone for periodontitis in a mouse model with the aim to c...

Characterizing Osteophyte Formation in Knee Osteoarthritis: Application of Machine Learning Quantification of a Computerized Tomography Cohort: Implications for Treatment.

BACKGROUND: Osteophytes are commonly used to diagnose and guide knee osteoarthritis (OA) treatment, but their causes are unclear. Although they are no...

A multiview deep learning-based prediction pipeline augmented with confident learning can improve performance in determining knee arthroplasty candidates.

PURPOSE: Preoperative prudent patient selection plays a crucial role in knee osteoarthritis management but faces challenges in appropriate referrals s...

A radiograph-based deep learning model improves radiologists' performance for classification of histological types of primary bone tumors: A multicenter study.

PURPOSE: To develop a deep learning (DL) model for classifying histological types of primary bone tumors (PBTs) using radiographs and evaluate its cli...

Collaborative hunting in artificial agents with deep reinforcement learning.

Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hu...

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderly. This investigation aims to develop an electromy...

Utilizing a comprehensive machine learning approach to identify patients at high risk for extended length of stay following spinal deformity surgery in pediatric patients with early onset scoliosis.

PURPOSE: Early onset scoliosis (EOS) patient diversity makes outcome prediction challenging. Machine learning offers an innovative approach to analyze...

Anthropomorphic Tendon-Based Hands Controlled by Agonist-Antagonist Corticospinal Neural Network.

This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural networ...

Development and validation of a machine learning model to improve precision prediction for irrational prescriptions in orthopedic perioperative patients.

OBJECTIVE: Our objective was to develop a machine learning model capable of predicting irrational medical prescriptions precisely within orthopedic pe...

Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model.

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intr...

Deep Omni-Supervised Learning for Rib Fracture Detection From Chest Radiology Images.

Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. ...

Precision in Prevention: Tailoring Single-Use Negative Pressure Wound Therapy Utilization Through Artificial Intelligence-Based Surgical Site Complications Risk and Cost Modeling.

Surgical site complications (SSCs) are common, yet preventable hospital-acquired conditions. Single-use negative pressure wound therapy (sNPWT) has b...