Orthopedics

Dynamic bone recognition for robotic vertebral plate cutting via unit energy consumption and SVM optimized by PSO.

Current orthopedic robots lack the ability to dynamically sense or accurately recognize bone layers during vertebral plate decompression surgery, limiting their ability to adjust actions in real time as skilled surgeons do. This study aims to improve robotic vertebral plate cutting by developing a bone recognition model that utilizes a unit energy consumption feature vector and support vector mach...

A Call for Integrated Approaches in Digital Technology Design for Aging and Disability.

The fields of aging and disability often proceed as 2 distinct lines of inquiry and action in terms of digital technology design. Guidelines and standards in both spaces (e.g., web content accessibility guidelines) have had suboptimal impact due to limited comprehensiveness enforcement mechanisms. Standards also rarely account for variations within the disability and aging communities and the stru...

Application of artificial intelligence-based three dimensional digital reconstruction technology in precision treatment of complex total hip arthroplasty.

PURPOSE: To evaluate the predictive ability of AI HIP in determining the size and position of prostheses during complex total hip arthroplasty (THA). ...

3D CAVLA: Leveraging Depth and 3D Context to Generalize Vision Language Action Models for Unseen Tasks

Robotic manipulation in 3D requires learning an $N$ degree-of-freedom joint space trajectory of a robot manipulator. Robots must possess semantic an...

Is a 3-Minute Knee MRI Protocol Sufficient for Daily Clinical Practice? A SuperResolution Reconstruction Approach Using AI and Compressed Sensing.

The purpose of this study was to assess whether a 3-min 2D knee protocol can meet the needs for clinical application if using a SuperResolution recon...

Predicting Knee Osteoarthritis Severity from Radiographic Predictors: Data from the Osteoarthritis Initiative.

PURPOSE: In knee osteoarthritis (KOA) treatment, preventive measures to reduce its onset risk are a key factor. Among individuals with radiographicall...

Editorial Commentary: Deteriorated Quality and Medial Retraction of Tendon Following Acute Traumatic Rotator Cuff Tear Are Predictors of Retear After Arthroscopic Repair.

Rotator cuff tears are a common cause of shoulder pain and dysfunction, affecting up to 33% of the population, and approximately 250,000 arthroscopic ...

Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt

We propose a novel joint framework by integrating super-resolution and segmentation, called JointSeg, which enables the generation of 1-meter ISA ma...

Max-Min Secrecy Rate and Secrecy Energy Efficiency Optimization for RIS-Aided VLC Systems: RSMA Versus NOMA

Integrating VLC with the RIS significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to...

An automated hip fracture detection, classification system on pelvic radiographs and comparison with 35 clinicians.

Accurate diagnosis of orthopedic injuries, especially pelvic and hip fractures, is vital in trauma management. While pelvic radiographs (PXRs) are wid...

Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.

BACKGROUND: Knee osteoarthritis (KOA) is a prevalent chronic disease worldwide, and traditional treatment methods lack personalized adjustment for ind...

Machine learning-based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study.

PURPOSE: To evaluate machine learning-based survival model roles in predicting rehospitalization after hip fractures to improve reduce the burden on t...

Human versus machine: deciding on high-stakes surgery in possible Cauda Equina syndrome.

BACKGROUND CONTEXT: Cauda Equina Syndrome (CES) is a spine surgical urgency requiring prompt intervention to prevent neurological deficits. Accurate i...

Active Sampling for MRI-based Sequential Decision Making

Despite the superior diagnostic capability of Magnetic Resonance Imaging (MRI), its use as a Point-of-Care (PoC) device remains limited by high cost...

Model-based learning for joint channel estimationand hybrid MIMO precoding

Hybrid precoding is a key ingredient of cost-effective massive multiple-input multiple-output transceivers. However, setting jointly digital and ana...

[The computer-aided diagnosis model of middle ear cholesteatoma based on integrated convolutional neural networks].

Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to const...

Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction.

BACKGROUND: Revision total knee arthroplasty (rTKA) and revision total hip arthroplasty (rTHA) are among the most resource-intensive orthopaedic proce...

Limitations of Machine Learning-Based Feature Importance in Osteoarthritis Biomarker Discovery.

Comparing Artificial Intelligence-Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study.

BACKGROUND: Knee osteoarthritis is a prevalent, chronic musculoskeletal disorder that impairs mobility and quality of life. Personalized patient educa...

Path and Bone-Contour Regularized Unpaired MRI-to-CT Translation

Accurate MRI-to-CT translation promises the integration of complementary imaging information without the need for additional imaging sessions. Given...