Diagnostic Radiology

Artificial intelligence-based methods for fusion of electronic health records and imaging data.

Healthcare data are inherently multimodal, including electronic health records (EHR), medical images...

Deploying deep learning models on unseen medical imaging using adversarial domain adaptation.

The fundamental challenge in machine learning is ensuring that trained models generalize well to uns...

Preventing Artificial Intelligence in Medical Imaging From Perpetuating Health Care Biases and Disparities.

Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI).

OBJECTIVES: Artificial intelligence (AI) is seen as a major disrupting force in the future healthcar...

Artificial Intelligence in Lung Imaging.

Recently, interest and advances in artificial intelligence (AI) including deep learning for medical ...

Evaluation of Multimedia Courseware-Assisted Teaching Effect of Medical Images Based on the Deep Learning Algorithm.

In order to improve the dynamic evaluation ability of medical image multimedia courseware-assisted t...

The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.

Artificial intelligence (AI) is becoming more widespread within radiology. Capabilities that AI algo...

Artificial Intelligence in Oncological Hybrid Imaging.

BACKGROUND: Artificial intelligence (AI) applications have become increasingly relevant across a bro...

Point-of-care SARS-CoV-2 sensing using lens-free imaging and a deep learning-assisted quantitative agglutination assay.

The persistence of the global COVID-19 pandemic caused by the SARS-CoV-2 virus has continued to emph...

Superlative Feature Selection Based Image Classification Using Deep Learning in Medical Imaging.

Medical image recognition plays an essential role in the forecasting and early identification of ser...

Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT.

To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based at...

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there...

Attention-based generative adversarial network in medical imaging: A narrative review.

As a popular probabilistic generative model, generative adversarial network (GAN) has been successfu...

Machine Learning Model Drift: Predicting Diagnostic Imaging Follow-Up as a Case Example.

OBJECTIVE: Address model drift in a machine learning (ML) model for predicting diagnostic imaging fo...

Addressing fairness in artificial intelligence for medical imaging.

A plethora of work has shown that AI systems can systematically and unfairly be biased against certa...

Artificial intelligence in emergency radiology: A review of applications and possibilities.

Artificial intelligence (AI) applications in radiology have been rising exponentially in the last de...

Deep neural networks constrained by neural mass models improve electrophysiological source imaging of spatiotemporal brain dynamics.

Many efforts have been made to image the spatiotemporal electrical activity of the brain with the pu...

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside.

Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in ...

Design and Implementation of Trace Inspection System Based upon Hyperspectral Imaging Technology.

Trace inspection is a key technology for collecting crime scenes in the criminal investigation depar...

Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features.

The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rap...

Radiographers' knowledge, attitudes and expectations of artificial intelligence in medical imaging.

INTRODUCTION: Artificial intelligence (AI) is increasingly utilised in medical imaging systems and p...