This commentary aims to provide an overview of generative AI in medical imaging, discussing applications, challenges, and ethical considerations, while highlighting future research directions in this rapidly evolving field.doi:10.1007/s10916-023-01987-4Mohamad,Koohi-Moghadam...
The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity ...
Over time, there has been increased development and interest in the use of generative AI. Even in the medical field, researchers have proposed and continue to propose the use of generative AI for various tasks. Patient records are hard to come by, medical data available to researchers are ofte...
we are in a unique position: Clinicians can focus more on the medical question and the patient. They lose less time searching through the available data sets. This is just the beginning of our journey to generative AI."
The Next Frontier in Medicine and Patient CareWhat you’ll learnIs this live event for you?Schedule Generative AI has the potential to transform every aspect of healthcare—from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. Physicians are takin...
Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in healthcare, with the potential to revolutionize clinical decision-making and improve health outcomes. Generative AI, capable of generating new data such as
From medical imaging and diagnosis to drug discovery, patient monitoring, personalized medicine, and even customer care through chatbots, generative AI can do it all. While we’re some time away from robots replacing doctors and nurses, LLMs are getting close to being useful in the field. Acco...
From pharma R&D to the point-of-care, learn how generative AI can accelerate health innovations and improve patient outcomes.
In many clinical and research settings, the scarcity of high-quality medical imaging datasets has hampered the potential of artificial intelligence (AI) clinical applications. This issue is particularly pronounced in less common conditions, underrepresen
AI vs. Generative AI: Traditional AI relies on strict rules to perform fixed tasks with precision, while Generative AI, through machine learning, discovers patterns in data to create original content, pushing the bounds of AI innovation. Generative AI vs. Predictive AI: Predictive AI forecasts fut...