In part one of our look at AI’s inexorable march into medicine and wellness, we explored how AI enhances diagnostics, clinical infrastructure, and preventative care.
Start there for a primer on attitudes, regulations, and the underlying technology, including Lenovo’s role in everything from hospital administration to algorithm development.
All that powerful transformation serves as atoolfor both patients and provider–and that trend will continue over the next decade.
So if AI is unlikely to supplant trusted doctors and must accommodate patient data privacy, where will the big changes happen?
AI in Five Years: Smarter Machines and Virtual Assistant
Incremental jumps in technology will increase the ubiquity and strength of the examples above, but where will the real change happen?
Consider how much happens behind-the-scenes when working with a virtual assistant on your smartphone.
From voice recognition that learnsyourvoice to combing through live search results to leveraging past behaviors to sharing results across devices—this unfolds instantly and most of us never even consider the AI-poweredhow.
“Imagine you go to the hospital for a PET scan or MRI,” said Scott Tease, Lenovo’s executive director of High Performance Computing and Artificial Intelligence.
“Before the doctor or technician reviews the images, an algorithm will interpret the data and flag every irregularity.
This accelerates the caregivers’ efforts, draws their attention to issues, and helps ensure nothing is overlooked.
In fact, these processes are under review by regulatory bodies right now.”
Enhanced resolution and analysis will allow remote scanning and diagnosis — even of small and subtle symptoms.
Doctors may be more apt to embrace this use of AI, but what about the deluge of tracking data?
The prospect of health-tracking devices automatically pinging clinics with potential concerns raises more than a few eyebrows.
We may also see the growing demand for “convenience”—everything available at your fingertips through a website or app—reshape low-risk patient care.
Here, AI may lead to chatbot-style physician care, where a series of targeted questions combined with biometrics will help people find the right care.
Telemedicine, of course, made consulting a doctor from the comfort of home possible years ago, but an electronic physician could radically reduce cost.
Even if a real person steps in to review and approve, an AI-led interview and data assessment would certainly increase efficiency.
“Convenience, risk assessment, and accuracy all play a role.
We’re not likely to see the chatbot approach take over for anything with dangerous symptoms.”
AI in 10 Years: Personalized, Globally Accessible Medicine
Assume that the changes outlined so far march forward, driven by advances in technology and wider adoption.Misconceptions about AI will also continue to erode, and successful deployment of AI-assisted technology
Who can guess how fleets of autonomous vehicles smoothly navigating city streets and highways will change perception?
AI also notoriously employs a so-called “black box”—the essential genius of deep-learning unfolds behind a closed curtain.
We know the input and output, of course, but seldom the step-by-step process of the AI reaching its conclusion.
It can be difficult to trust an answer when the underlying work is hidden (and may contain accidental bias).
Trust will likely grow over the next decade, but even without that embrace, things may wildly transform—as much as possible in the regulated world of medicine.
Mapping a genome opens a window into inherited conditions, susceptibility to disease, potential response to treatment, and countless other insights.
But the process takes time and the considerable might of high-performance computers.
“A patient anywhere in the world could share a blood sample and deep biometrics,” he said