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If you’re searching for an industry that’s defined by innovation and technological progression, look no further than health care. Despite heavy regulations and high barriers to entry, this sector continues to see major breakthroughs 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 there are still significant challenges to overcome.

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 Schuetz, a senior data scientist at Sutter Health. “I don’t know if it’s two years or 10 — but it’s coming.”

Indeed, the innovation happening behind closed doors is astounding. However, technological, psychological, and regulatory limitations are holding the industry back.

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As we consider the state of AI in health care (and when the next breakthrough will occur), it’s helpful to identify some of the key opportunities and challenges in the present environment.

Significant technological limitations

The term “artificial intelligence” is often used to refer to a variety of 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 basic tasks, it can actually defeat humans in fairly complex scenarios. IBM Watson’s Jeopardy victory is a great example of this. When researchers can realistically introduce ANI into health care, the pieces will start to fall into place.

Convenience and savings will drive innovation

For AI to truly transform 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 provide 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 a “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.

Money isn’t the real problem

While there are certainly smaller companies and less-connected innovators who are having trouble funding their ideas, a lack of money isn’t AI’s biggest problem. Tech giants like IBM, Alphabet, Philips, and a variety of pharmaceutical companies are pouring billions of dollars into 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 reach $6.6 billion by 2021.

Early applications emphasize diagnoses

AI can go in dozens of different directions, but when you look at the present landscape, a few trends stand out.

“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. The company’s 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.”

It does 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.

A future in which AI and health care work together to provide exceptional, reliable, and cost-effective care isn’t far off. Competition in this space is heated as companies race to see who can deliver the most accurate and consistent results first. As soon as the industry removes some of the major challenges and roadblocks, growth will quickly follow.

Larry Alton is a contributing writer at VentureBeat covering artificial intelligence.

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