Diagnostic Radiology

Metabolomic profiling and accurate diagnosis of basal cell carcinoma by MALDI imaging and machine learning.

Basal cell carcinoma (BCC), the most common keratinocyte cancer, presents a substantial public healt...

Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.

The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Ass...

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update.

To address the rapid evolution of artificial intelligence in medical imaging, the authors present th...

Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.

BACKGROUND: This study evaluated whether generative artificial intelligence (AI)-based augmentation ...

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands o...

Randomised controlled trials evaluating artificial intelligence in clinical practice: a scoping review.

This scoping review of randomised controlled trials on artificial intelligence (AI) in clinical prac...

Invited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial Intelligence.

Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.

The Radiological Society of North America (RSNA) has held artificial intelligence competitions to ta...

The diagnostic, therapeutic, and ethical impact of artificial intelligence in modern medicine.

In the evolution of modern medicine, artificial intelligence (AI) has been proven to provide an inte...

Opinion: Big Data Elements Key to Medical Imaging Machine Learning Tool Development.

Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals.

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, h...

Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT.

Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors o...

AI in imaging: the regulatory landscape.

Artificial intelligence (AI) methods have been applied to medical imaging for several decades, but i...

Artificial Intelligence in Medical Imaging: An Overview of a Decade of Experience.

Diagnostic-therapeutic management of pulmonary nodules.

BACKGROUND: Lung cancer is one of the leading causes of death worldwide, with incidence and mortalit...

Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations.

BACKGROUND: The emergence of deep learning (DL) techniques has revolutionized tumor detection and cl...

Artificial Intelligence in Bone Metastasis Imaging: Recent Progresses from Diagnosis to Treatment - A Narrative Review.

The introduction of artificial intelligence (AI) represents an actual revolution in the radiological...

Chapter 9. Return to the revision of the bioethics law regarding the use of artificial intelligence in the field of medical imaging.

On the occasion of the sixth AI international Summit (November 22-24, 2023), Professor Daniel Ruecke...

Performance of ChatGPT on the Brazilian Radiology and Diagnostic Imaging and Mammography Board Examinations.

This prospective exploratory study conducted from January 2023 through May 2023 evaluated the abilit...

Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology.

Despite recent advancements in machine learning (ML) applications in health care, there have been fe...

Early experiences of integrating an artificial intelligence-based diagnostic decision support system into radiology settings: a qualitative study.

OBJECTIVES: Artificial intelligence (AI)-based clinical decision support systems to aid diagnosis ar...