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

AR Katwaroo, VS Adesh, A Lowtan… - Postgraduate medical …, 2024‏ - academic.oup.com
In the evolution of modern medicine, artificial intelligence (AI) has been proven to provide an
integral aspect of revolutionizing clinical diagnosis, drug discovery, and patient care. With …

Position statements of the emerging trends committee of the Asian Oceanian Society of Radiology on the adoption and implementation of artificial intelligence for …

NK Wee, KA Git, WJ Lee, G Raval… - Korean Journal of …, 2024‏ - pmc.ncbi.nlm.nih.gov
Artificial intelligence (AI) is rapidly gaining recognition in the radiology domain as a greater
number of radiologists are becoming AI-literate. However, the adoption and implementation …

Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects

B Koçak, A Ponsiglione, A Stanzione… - Diagnostic and …, 2024‏ - zora.uzh.ch
Although artificial intelligence (AI) methods hold promise for medical imaging-based
prediction tasks, their integration into medical practice may present a double-edged sword …

Enhancing semantic segmentation in chest X-ray images through image preprocessing: ps-KDE for pixel-wise substitution by kernel density estimation

Y Wang, Y Guo, Z Wang, L Yu, Y Yan, Z Gu - Plos one, 2024‏ - journals.plos.org
Background In medical imaging, the integration of deep-learning-based semantic
segmentation algorithms with preprocessing techniques can reduce the need for human …

Mitigating the risk of health inequity exacerbated by large language models

Y Ji, W Ma, S Sivarajkumar, H Zhang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Recent advancements in large language models have demonstrated their potential in
numerous medical applications, particularly in automating clinical trial matching for …

Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays

K Arzamasov, Y Vasilev, M Zelenova… - … Imaging in Medicine …, 2024‏ - pmc.ncbi.nlm.nih.gov
Background The integration of artificial intelligence (AI) into medicine is growing, with some
experts predicting its standalone use soon. However, skepticism remains due to limited …

The potential of large language models for radiology report simplification and translations

S Tripathi, F Dako - Journal of the American College of Radiology, 2024‏ - Elsevier
Effective communication lies at the heart of quality patient-centered healthcare, especially
within specialized fields like radiology1. Radiology reports, replete with intricate medical …

PRECISE framework: GPT-based text for improved readability, reliability, and understandability of radiology reports for patient-centered care

S Tripathi, L Mutter, M Muppuri, S Dheer… - arxiv preprint arxiv …, 2024‏ - arxiv.org
This study introduces and evaluates the PRECISE framework, utilizing OpenAI's GPT-4 to
enhance patient engagement by providing clearer and more accessible chest X-ray reports …

Self-supervised learning for chest computed tomography: training strategies and effect on downstream applications

A Tariq, G Ramasamy, B Patel… - Journal of Medical …, 2024‏ - spiedigitallibrary.org
Purpose Self-supervised pre-training can reduce the amount of labeled training data
needed by pre-learning fundamental visual characteristics of the medical imaging data. We …

The US Government's Latest Presidential Executive Order on Artificial Intelligence: Potential Implications in Radiology

RM Treat, SK Hsiao, A Ismail, R Javan - Journal of the American College of …, 2024‏ - Elsevier
During the preparation of this work the author (s) used Anthropic's Claude 2 in order to
improve overall readability and assist with itemized summarization. After using this …