Diagnostic Radiology

Artificial Intelligence to Improve Patient Understanding of Radiology Reports.

Diagnostic imaging reports are generally written with a target audience of other providers. As a res...

Imaging Analytics using Artificial Intelligence in Oncology: A Comprehensive Review.

The present era has seen a surge in artificial intelligence-related research in oncology, mainly usi...

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMA...

Diagnostic performance of a novel deep learning attenuation correction software for MPI using a cardio dedicated CZT camera. Experience in the clinical practice.

PURPOSE: To evaluate the diagnostic performance of a novel deep learning attenuation correction soft...

Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM.

OBJECTIVE: To evaluate the usage of a well-known and widely adopted checklist, Checklist for Artific...

Understanding calibration of deep neural networks for medical image classification.

Background and Objective - In the field of medical image analysis, achieving high accuracy is not en...

AI in medical imaging grand challenges: translation from competition to research benefit and patient care.

Artificial intelligence (AI), in one form or another, has been a part of medical imaging for decades...

High resolution imaging and analysis of extracellular vesicles using mass spectral imaging and machine learning.

Extracellular vesicles (EVs) are potentially useful biomarkers for disease detection and monitoring....

Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013-2023).

Uncertainty estimation in healthcare involves quantifying and understanding the inherent uncertainty...

Generative AI in Medical Imaging: Applications, Challenges, and Ethics.

Medical imaging is playing an important role in diagnosis and treatment of diseases. Generative arti...

New trend in artificial intelligence-based assistive technology for thoracic imaging.

Although there is no solid agreement for artificial intelligence (AI), it refers to a computer syste...

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary.

Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically eva...

"Shortcuts" Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation.

Despite the expert-level performance of artificial intelligence (AI) models for various medical imag...

Use of Artificial Intelligence in Radiology: Impact on Pediatric Patients, a White Paper From the ACR Pediatric AI Workgroup.

In this white paper, the ACR Pediatric AI Workgroup of the Commission on Informatics educates the ra...

Generative Adversarial Networks in Medicine: Important Considerations for this Emerging Innovation in Artificial Intelligence.

The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of...

The Role of Organized Radiology in Advancing Imaging Artificial Intelligence.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets.

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides ...

Understanding Biases and Disparities in Radiology AI Datasets: A Review.

Artificial intelligence (AI) continues to show great potential in disease detection and diagnosis on...

A Patient's Wish List for Imaging Artificial Intelligence (and Radiology).

Artificial intelligence for detecting temporomandibular joint osteoarthritis using radiographic image data: A systematic review and meta-analysis of diagnostic test accuracy.

In this review, we assessed the diagnostic efficiency of artificial intelligence (AI) models in dete...

A Survey on Artificial Intelligence in Pulmonary Imaging.

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and ima...