AI Medical Compendium Journal:
Journal of medical imaging and radiation sciences

Showing 1 to 10 of 41 articles

Artificial Intelligence user interface preferences in radiology: A scoping review.

Journal of medical imaging and radiation sciences
INTRODUCTION/BACKGROUND: Modern forms of Artificial intelligence (AI) have developed in radiology over the past few years. With the current workforce shortages, in both radiology and radiography professions, AI continues to prove its place in support...

Artificial intelligence education in medical imaging: A scoping review.

Journal of medical imaging and radiation sciences
BACKGROUND: The rise of Artificial intelligence (AI) is reshaping healthcare, particularly in medical imaging. In this emerging field, clinical imaging personnel need proper training. However, formal AI education is lacking in medical curricula, coup...

Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial Intelligence (AI) has the potential to transform medical imaging and radiotherapy; both fields where radiographers' use of AI tools is increasing. This study aimed to explore the views of those professionals who are now using...

For the busy clinical-imaging professional in an AI world: Gaining intuition about deep learning without math.

Journal of medical imaging and radiation sciences
Medical diagnostics comprise recognizing patterns in images, tissue slides, and symptoms. Deep learning algorithms (DLs) are well suited to such tasks, but they are black boxes in various ways. To explain DL Computer-Aided Diagnostic (CAD) results an...

Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there hav...

The knowledge and perception of patients in Malta towards artificial intelligence in medical imaging.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial intelligence (AI) is becoming increasingly implemented in radiology, especially in image reporting. Patients' perceptions about AI integration in medical imaging is a relatively unexplored area that has received limited inves...

Artificial intelligence and advanced MRI techniques: A comprehensive analysis of diffuse gliomas.

Journal of medical imaging and radiation sciences
INTRODUCTION: The complexity of diffuse gliomas relies on advanced imaging techniques like MRI to understand their heterogeneity. Utilizing the UCSF-PDGM dataset, this study harnesses MRI techniques, radiomics, and AI to analyze diffuse gliomas for o...

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing.

Journal of medical imaging and radiation sciences
BACKGROUND: The reproducibility crisis in AI research remains a significant concern. While code sharing has been acknowledged as a step toward addressing this issue, our focus extends beyond this paradigm. In this work, we explore "federated testing"...

Perspectives of medical imaging professionals about the impact of AI on Swiss radiographers.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial Intelligence (AI) is increasingly implemented in medical imaging practice, however, its impact on radiographers practice is not well studied. The aim of this study was to explore the perceived impact of AI on radiographers' a...

Ethical, legal, and regulatory landscape of artificial intelligence in Australian healthcare and ethical integration in radiography: A narrative review.

Journal of medical imaging and radiation sciences
This narrative review explores the ethical, legal, and regulatory landscape of AI integration in Australian healthcare, focusing on radiography. It examines the current legislative framework, assesses the trust and reliability of AI tools, and propos...