After announcing the launch of AIMed Cardiology this Valentine’s Day, AIMed hoorays the arrival of AIMed Radiology, to take place between 18 and 19 June at Ritz-Carlton, Chicago, Illinois. The one and a half day event will expose attendees to the future of radiology. It will also encourage them to be part of an ongoing revolution which set out to transform present-day medicine.
Specifically, AIMed Radiology brings together healthcare professionals, researchers, technology experts
AIMed Radiology is believed to be the number one event of its type in US. The initiative aims to prepare the field for an AI-inspired future and facilitate a similar change in medical education, as more and more likeminded express their interests to come on board.
How is AI transforming radiology?
To some of the experts whom we interviewed at this year’s Healthcare Information and Management Systems Society (HIMSS) conference, the future of radiology has already arrived. They agreed that AI reduces the amount of variability in radiology, enabling it to be more efficient and accurate. In some ways, AI is also cutting down cost as certain reading like mammography, no longer have to be read by two radiologists. There is now the option of employing one human radiologist and an AI to do the job. This is especially so as some of the provided solutions focus on workflow integration.
Besides, AI brings attention to radiologists more quickly and meaningfully. In the past, emergency decides whether or not the images will be attended first. With AI, it moves beyond what human are able to do: that is to make use of existing information to obtain more information. This ensure diagnosis and treatment are more acutely provided to a patient.
Challenges and barriers ahead
Interestingly, nearly all the experts who AIMed spoke to, mentioned that data is hindering AI to exercise its full potential on radiology. As most databases and hospital resources are not connected, sometimes, it can be extremely challenging for developers to collect quality data. The broader the demographics and diversity expressed in the data, the more robust the eventual algorithm can be generated.
Even if it can be done, curating the data is posing a separate set of problems. Curating refers to differentiating the good data from the bad, there is a need to bring in radiologists, to be certain that when the algorithm says cancer is present, the patient is truly coming with cancer and vice versa.
Others mentioned the challenges coming from regulations as there is a need to go through
So why is AIMed launching AIMed Radiology?
Ultimately, for those who knew what is going on, they hope others are able to better understand the benefits behind adopting AI into radiology. There has been a lot of hype and people are generally excited about it. This is the reason why AIMed is kick starting the conversation, to bring interested parties into the playing field and hope that AI does not stay virtual but it truly influences the real World.
As AI in radiology moves from algorithmic focus to outcome focus, there is a demand being put on resources, skills
A science writer with data background and an interest in current affair, culture and arts; a no-med from an (almost) all-med family. Follow on Twitter.