Artificial Intelligence and Workforce Diversity in Nuclear Medicine DOI Creative Commons
K. Elizabeth Hawk, Geoffrey Currie

Seminars in Nuclear Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, integration AI into medicine education, clinical practice, and research a significant impact on workforce diversity. While in potential to be powerful tool improve clinical, educational enhance patient care, careful examination each needs undertaken with respect on, among other factors, diversity workforce. Some tools can used specifically drive inclusivity by supporting women underrepresented minorities. Other tools, however, have negatively minority groups, leading widening gap. This manuscript explores how various solutions both positively affect

Language: Английский

The Evolution of Artificial Intelligence in Nuclear Medicine DOI Creative Commons
Leonor Lopes, Alejandro López-Montes, Yizhou Chen

et al.

Seminars in Nuclear Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Nuclear medicine has continuously evolved since its beginnings, constantly improving the diagnosis and treatment of various diseases. The integration artificial intelligence (AI) is one latest revolutionizing chapters, promising significant advancements in diagnosis, prognosis, segmentation, image quality enhancement, theranostics. Early AI applications nuclear focused on diagnostic accuracy, leveraging machine learning algorithms for disease classification outcome prediction. Advances deep learning, including convolutional more recently transformer-based neural networks, have further enabled precise segmentation as well low-dose imaging, patient-specific dosimetry personalized treatment. Generative AI, driven by large language models diffusion techniques, now allowing process, interpretation, generation complex medical images. Despite these achievements, challenges such data scarcity, heterogeneity, ethical concerns remain barriers to clinical translation. Addressing issues through interdisciplinary collaboration will pave way a broader adoption medicine, potentially enhancing patient care optimizing therapeutic outcomes.

Language: Английский

Citations

1
Radiopharmaceuticals in nasopharyngeal Cancer DOI
Xiao‐Quan Xu, Xuemei Tang,

Wan-yin Wu

et al.

Bioorganic Chemistry, Journal Year: 2025, Volume and Issue: 157, P. 108281 - 108281

Published: Feb. 14, 2025

Language: Английский

Citations

1
Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms DOI
Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Keng‐Boon Ooi

et al.

Computers in Industry, Journal Year: 2024, Volume and Issue: 161, P. 104128 - 104128

Published: July 21, 2024

Language: Английский

Citations

5
Twelve tips on applying AI tools in HPE scholarship using Boyer’s model DOI
Jennifer Benjamin, Ken Masters, Anoop Agrawal

et al.

Medical Teacher, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 6

Published: Jan. 10, 2025

AI has changed the landscape of health professions education. With hype now behind us, we find ourselves in phase reckoning, considering what's next; where do start and how can educators use these powerful tools for daily teaching learning. We recognize great need training to meaningfully Boyer's model scholarship provides a pedagogical approach with maximize efforts towards scholarship. By offering practical solutions demonstrating their usefulness, this Twelve tips article demonstrates apply by leveraging capabilities tools. Despite potential, our recommendation is exercise caution against dependency role responsible evaluating outputs critically commitment accuracy scrutinize hallucinations false citations.

Language: Английский

Citations

0
Generative Artificial Intelligence in Nuclear Medicine Education DOI
Geoffrey Currie

Journal of Nuclear Medicine Technology, Journal Year: 2025, Volume and Issue: 53(1), P. 72 - 79

Published: Feb. 5, 2025

Generative artificial intelligence (genAI) has become assimilated into the education, research, and clinical domains of nuclear medicine health care. Understanding principles, limitations, applications genAI is important for capitalizing on its transformative potential in student education impact sustainability within both sectors. In this article, fundamental principles are explored from context medicine. GenAI technologies defined capabilities outlined. A detailed investigation limitations text-to-text text-to-image based empiric anecdotal research provided. Specific examples to reinvigorate by supporting enriching learning be but at time writing, far revolutionary. Nonetheless, horizon promises genAI. can enhance provide economies improve Although there some current capabilities, rapidly evolving space will soon offer benefits education.

Language: Английский

Citations

0
Using artificial intelligence in health research DOI
Daniel Rodger, Siobhán O’Connor

Evidence-Based Nursing, Journal Year: 2025, Volume and Issue: unknown, P. ebnurs - 104287

Published: Feb. 27, 2025

Language: Английский

Citations

0
From data to perception: visualizing bias in artificial intelligence-generated images DOI
Piotr Szymański, Magdalena Lipczyńska, Anna Górska

et al.

European Heart Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 20, 2025

Citations

0
Letter from the Editors DOI
Kirsten Bouchelouche, Mike Sathekge

Seminars in Nuclear Medicine, Journal Year: 2025, Volume and Issue: 55(3), P. 291 - 293

Published: April 15, 2025

Language: Английский

Citations

0
Potential Applications and Ethical Considerations for Artificial Intelligence in Traumatic Brain Injury Management DOI Creative Commons

Kryshawna Beard,

Ashley M. Pennington,

Amina K. Gauff

et al.

Biomedicines, Journal Year: 2024, Volume and Issue: 12(11), P. 2459 - 2459

Published: Oct. 26, 2024

Artificial intelligence (AI) systems have emerged as promising tools for rapidly identifying patterns in large amounts of healthcare data to help guide clinical decision making, well assist with medical education and the planning research studies. Accumulating evidence suggests AI techniques may be particularly useful aiding diagnosis management traumatic brain injury (TBI)—a considerably heterogeneous neurologic condition that can challenging detect treat. However, important methodological ethical concerns use medicine necessitate close monitoring regulation these advancements continue. The purpose this narrative review is provide an overview common describe recent studies on possible applications context TBI. Finally, describes challenges medicine, guidelines from White House, Department Defense (DOD), National Academies Sciences, Engineering, Medicine (NASEM), other organizations appropriate uses research.

Language: Английский

Citations

3
Artificial Intelligence and Workforce Diversity in Nuclear Medicine DOI Creative Commons
K. Elizabeth Hawk, Geoffrey Currie

Seminars in Nuclear Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, integration AI into medicine education, clinical practice, and research a significant impact on workforce diversity. While in potential to be powerful tool improve clinical, educational enhance patient care, careful examination each needs undertaken with respect on, among other factors, diversity workforce. Some tools can used specifically drive inclusivity by supporting women underrepresented minorities. Other tools, however, have negatively minority groups, leading widening gap. This manuscript explores how various solutions both positively affect

Language: Английский

Citations

1