We talked to Dr. Bertalan Meskó, AKA The Medical Futurist, about the latest MedTech trends he’s keeping an eye on. Here’s what he had to say:
What recent advancements in MedTech are you most excited about?
By far, the most exciting recent advancement in medical technology is generative AI, especially large language models (LLMs). Generative AI represents a new category of AI that can create new text, images, videos, and sound by looking for patterns and structures in the sample dataset. From our human perspective, this looks intuitive and creative.
In healthcare, studies have demonstrated that LLMs could help physicians save time while doing administrative tasks; and replace repetitive processes. For patients, LLMs could help interpret laboratory results or discharge notes, among many other examples.
Moreover, as LLMs become multimodal (being able to deal with different types of data such as text, image, video, and sound), these could become a gateway for physicians for using AI.
They would only have to learn to interact with one platform through a skillset called prompt engineering, and they would be able to benefit from using a range of AI-based services and technologies.
This could represent a new era in which deploying AI just became much simpler than before.
How is AI being used in healthcare right now?
We published a study about which medical specialties stand out regarding the impact of AI and cardiology, oncology, and radiology were the prime examples. The general rule of thumb is that it seems these specialties might entail more repetitive and data-based tasks than the others, thus these are more prone to automation.
Besides these, AI is being used to reduce the time spent on administration, to assist medical decision-making, flag complex cases for radiologists, identify signs of cancer on CT scans, or help find the most personalized treatment for a type of cancer. The list goes on, and there are already almost 700 AI-based medical technologies approved by the FDA, and the database keeps on growing.
How can these applications of AI help improve patient outcomes?
To improve patient outcomes, you need data, an active role from patients in their disease management, and more time and attention from their medical professionals. All these are being supported by AI-based technologies.
Algorithms in radiology, genomics, and devices like smartphone-connected ultrasound are supported by AI. There are smartphone-connected ECG sensors that can analyze a user’s data immediately with AI. There are developers of smartphones that try to exploit the benefits of AI to provide patients with clinically more useful data.
Without AI sharing suggestions and lifestyle insights, patients just keep on obtaining data they cannot do anything with. It’s very easy to feel doomed with all the information patients can measure about themselves with fitness trackers and portable diagnostic devices, therefore, there is a growing market for platforms that try to make sense of the data. This is an important part of patients becoming engaged with their care, which is the key part of the cultural paradigm shift we call digital health.
And regarding time and attention from medical professionals, you can only improve that if they don’t have to dedicate their human expertise, vision, and creativity to repetitive and data-based tasks.
In summary, it’s not that AI technologies could improve patient outcomes, but AI seems to be our only viable option to achieve that goal in the age of data and information.
Is there anything else you’d like our readers to know about innovations in MedTech or AI for healthcare?
The end of the paradigm shift called digital health will be patients becoming the point-of-care. Wherever they are, they should be able to access healthcare, and receive diagnosis, monitoring, and treatment. During this process, healthcare becomes globalized and medicine becomes more dependent on the use of advanced technologies.
However, the next paradigm shift is imminent, too. In that, this new medical team consisting of patients and medical professionals on an equal-level partnership will get a new member: a technological entity called AI.
That is going to raise a range of unsolved challenges and ethical issues. The reason why we will have to deal with them is because the potential of that breakthrough technology still outweighs the risks.
