The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the development of deep learning models tailored for specific imaging tasks. Additionally, the advent of multimodal foundational models, capable of generating images, text and videos, presents a broad spectrum of applications within ophthalmology. These range from enhancing diagnostic accuracy to improving patient education and training healthcare professionals. Despite the promising potential, this area of technology is still in its infancy, and there are several challenges to be addressed, including data bias, safety concerns and the practical implementation of these technologies in clinical settings.
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http://dx.doi.org/10.1136/bjo-2024-325458 | DOI Listing |
Sci Rep
January 2025
Division of Critical Care Medicine, Department of Emergency Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong-si, Gyeonggi-do, Republic of Korea.
The optimal duration of on-scene cardiopulmonary resuscitation (CPR) for out-of-hospital cardiac arrest (OHCA) patients remains uncertain. Determining this critical time period requires outweighing the potential risks associated with intra-arrest transport while minimizing delays in accessing definitive hospital-based treatments. This study evaluated the association between on-scene CPR duration and 30-day neurologically favorable survival based on the transport time interval (TTI) in patients with OHCA.
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January 2025
Department of Electrical Power, Adama Science and Technology University, Adama, 1888, Ethiopia.
Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision.
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January 2025
School of Medicine, Anhui University of Science and Technology, Huainan, 232001, China.
Ultrasound is a primary diagnostic tool commonly used to evaluate internal body structures, including organs, blood vessels, the musculoskeletal system, and fetal development. Due to challenges such as operator dependence, noise, limited field of view, difficulty in imaging through bone and air, and variability across different systems, diagnosing abnormalities in ultrasound images is particularly challenging for less experienced clinicians. The development of artificial intelligence (AI) technology could assist in the diagnosis of ultrasound images.
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January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFJ Med Ethics
January 2025
Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Introduction: The integration of artificial intelligence (AI) into healthcare introduces innovative possibilities but raises ethical, legal and professional concerns. Assessing the performance of AI in core components of the United States Medical Licensing Examination (USMLE), such as communication skills, ethics, empathy and professionalism, is crucial. This study evaluates how well ChatGPT versions 3.
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