A practical guide to the development and deployment of deep learning models for the Orthopedic surgeon: part I
Deep learning has a profound impact on daily life. As Orthopedics makes use of this rapid
escalation in technology, Orthopedic surgeons will need to take leadership roles on deep …
escalation in technology, Orthopedic surgeons will need to take leadership roles on deep …
A practical guide to the development and deployment of deep learning models for the orthopaedic surgeon: Part III, focus on registry creation, diagnosis, and data …
Deep learning is a subset of artificial intelligence (AI) with enormous potential to transform
orthopaedic surgery. As has already become evident with the deployment of Large …
orthopaedic surgery. As has already become evident with the deployment of Large …
Anonymizing radiographs using an object detection deep learning algorithm
Radiographic markers contain protected health information that must be removed before
public release. This work presents a deep learning algorithm that localizes radiographic …
public release. This work presents a deep learning algorithm that localizes radiographic …
THA-AID: deep learning tool for total hip arthroplasty automatic implant detection with uncertainty and outlier quantification
Background Revision total hip arthroplasty (THA) requires preoperatively identifying in situ
implants, a time-consuming and sometimes unachievable task. Although deep learning (DL) …
implants, a time-consuming and sometimes unachievable task. Although deep learning (DL) …
Few-shot biomedical image segmentation using diffusion models: Beyond image generation
Background Medical image analysis pipelines often involve segmentation, which requires a
large amount of annotated training data, which is time-consuming and costly. To address …
large amount of annotated training data, which is time-consuming and costly. To address …
Creating high fidelity synthetic pelvis radiographs using generative adversarial networks: unlocking the potential of deep learning models without patient privacy …
Background In this work, we applied and validated an artificial intelligence technique known
as generative adversarial networks (GANs) to create large volumes of high-fidelity synthetic …
as generative adversarial networks (GANs) to create large volumes of high-fidelity synthetic …
Deep learning to automatically classify very large sets of preoperative and postoperative shoulder arthroplasty radiographs
Background Joint arthroplasty registries usually lack information on medical imaging owing
to the laborious process of observing and recording, as well as the lack of standard methods …
to the laborious process of observing and recording, as well as the lack of standard methods …
Patient-specific hip arthroplasty dislocation risk calculator: an explainable multimodal machine learning–based approach
Purpose To develop a multimodal machine learning–based pipeline to predict patient-
specific risk of dislocation following primary total hip arthroplasty (THA). Materials and …
specific risk of dislocation following primary total hip arthroplasty (THA). Materials and …
Implications of pediatric artificial intelligence challenges for artificial intelligence education and curriculum development
Several radiology artificial intelligence (AI) courses are offered by a variety of institutions and
educators. The major radiology societies have developed AI curricula focused on basic AI …
educators. The major radiology societies have developed AI curricula focused on basic AI …
THA-net: a deep learning solution for next-generation templating and patient-specific surgical execution
Background This study introduces THA-Net, a deep learning inpainting algorithm for
simulating postoperative total hip arthroplasty (THA) radiographs from a single preoperative …
simulating postoperative total hip arthroplasty (THA) radiographs from a single preoperative …