GUEST:
If you’re searching for an industry that’s defined by innovation and technological progression, look no further than health care. The health care industry is the poster child for the application of new technology. Despite heavy regulations and high barriers to entry, it continues to be a sector where major breakthroughs happen on a regular basis.
So, is the health care industry ready for a breakthrough when it comes to artificial intelligence? The building blocks are in place, and opportunities certainly exist, but can the industry overcome significant challenges?
The rise of AI
“I have no doubt that sophisticated learning and AI algorithms will find a place in health care over the coming years,” says Andy Shuetz, a senior data scientist at Sutter Health. “I don’t know if it’s two years or ten – but it’s coming.”
Shuetz hits the proverbial nail on the head with this statement. Nobody doubts AI and health care will be intertwined for decades to come. The only uncertainty is when it’ll explode onto the scene.
The best way to describe the current state of AI in health care is by looking at an analogy of a big balloon filled with air. The air, being AI innovation, wants to escape the balloon and disperse into the environment which would be the health care industry in this scenario. But the latex balloon, which represents the industry challenges, is holding the air inside.
The metaphorical balloon isn’t tied, though. Instead, there’s someone holding the mouth of the balloon between two fingers. Every so often, the fingers loosen and some air seeps out. Then they close again, and the remaining air stays trapped inside.
While all the air will eventually leak out via this process, it’s slow and inefficient. What really needs to happen is for someone to grab a needle, the smallest will do, and puncture the latex. Once this happens, the balloon will collapse, and the air will rapidly rush out.
There’s so much potential for AI in the medical field. The innovation happening behind closed doors is astounding. However, there are still technological, psychological, and regulatory limitations and challenges holding things back. A breakthrough is imminent. The only question is when?
Opportunities and challenges worth watching
As we consider where things stand with AI in health care (and when the next breakthrough will occur), it’s helpful to identify some of the key opportunities and challenges that exist in the present environment.
1. There are still significant technological limitations
When people use the term “artificial intelligence,” they’re often referring to various machine learning methods. In order for AI to really make a significant difference, it’s important that we reach artificial narrow intelligence (ANI).
ANI does more than complete tasks, it can actually defeat humans in specific tasks. IBM’s Watson winning Jeopardy is a great example of this. When researchers can realistically introduce ANI into health care, that’s when the pieces will start to fall into place.
2. Cost and convenience will drive initial innovation
For AI to truly become transformational in health care, innovation needs to be centered on two key factors: cost and convenience. Both doctors and patients want to see costs go down and convenience go up. Technologists and companies that can do both will thrive.
iCliniq is a good example of a company that’s using AI to lower costs and increase convenience in the health care space. Labeled as “the virtual hospital,” iCliniq gives users access to doctors, medical advice, and second opinions from licensed health care professionals all over the world. It uses AI to help doctors answer patients’ queries faster, which brings down the cost of consultations and makes health care more affordable and readily available.
As more entrepreneurs and tech companies focus on cost and convenience, we’ll see greater acceptance in the marketplace. In turn, this will open new doors and increase pressure on those in leadership positions to make room for AI.
3. Money isn’t a problem
While there are certainly some smaller companies and less connected innovators who are having trouble funding their ideas, money really isn’t a problem with AI. Tech giants like IBM, Alphabet, Philips, and a variety of pharmaceutical companies are pouring billions of dollars into various startups and products. According to estimates from Frost & Sullivan, the market for AI in health care and life sciences is expected to grow by 40 percent per year, to $ 6.6 billion by 2021.
4. Early applications emphasizing diagnoses
AI can go in dozens of different directions, but when you take an expansive look at the present landscape, it’s easy to identify the bigger trends.
“To date, the sweet spot in health care AI has been pairing algorithms with structured exercises in reading patient data and medical images to train machines to detect abnormalities. This training is called ‘deep learning,’” health care consultant Brian Scogland explains. “In the same way, algorithms are being used to sift through vast amounts of medical literature to inform treatment decisions where it would be too onerous a task to have a human read through the same journals.”
MedyMatch is a great example of a company that’s finding success in this space. Their goal is to “[Bring] accuracy to physicians and capacity to health care to prevent chronic conditions and improve patient outcomes with the right treatment at the right time.”
They do this by creating AI-driven diagnostic tools that leverage 3D imaging, patient-specific data, and machine learning to deliver precise advice that medical teams can use to improve care.
The competition in this space is heated and there’s a race to see who can deliver the most accurate and consistent results first. We should view this high level of competition as a positive thing for everyone involved.
The future of medicine is near
A future where AI and health care harmoniously work together to provide exceptional, reliable, and cost-effective care to communities and their patients isn’t far off. As some of today’s technologies prove, the innovation is already here. As soon as the industry removes some of the major challenges and roadblocks, growth will follow.
Larry Alton is a contributing writer at VentureBeat covering artificial intelligence.
