Healthcare is just as prone to fall victim to hype and irrational exuberance as any other complex industry. And the more revolutionary the promise, the more outrageous the overstatements could be. Artificial intelligence has certainly been one of those "next big things" for some time in healthcare. Whether branded as "big data and analytics" or "automated clinical decision support," the results of technology-assisted care, especially in non-clinical and non-emergent settings, have been uneven at best. But a new report indicates AI's time in healthcare is nigh, and technology and policy pioneers are doing their best to ensure the hopes aren't all hype.

Since entrepreneur Chris Mansi cofounded Viz.ai in 2016, the best-funded wizards of artificial intelligence have taken on board games, and created emoji that mirror your facial expressions. Meanwhile, Mansi has been developing algorithms to save the brain cells of stroke patients. This month, the Food and Drug Administration cleared Viz.ai to market its algorithms to doctors and hospitals. It was a small breakthrough toward using AI to make healthcare more efficient and powerful. Someone in the US suffers a stroke every 40 seconds, according to the Centers for Disease Control.

The computer will see you now. Artificial intelligence algorithms may soon bring the diagnostic know-how of an eye doctor to primary care offices and walk-in clinics, speeding up the detection of health problems and the start of treatment, especially in areas where specialized doctors are scarce. The first such program -- trained to spot symptoms of diabetes-related vision loss in eye images -- is pending approval by the U.S. Food and Drug Administration. While other already approved AI programs help doctors examine medical images, there's "not a specialist looking over the shoulder of [this] algorithm," says Michael Abràmoff, who founded and heads a company that developed the system under FDA review, dubbed IDx-DR. "It makes the clinical decision on its own."

This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in non-coding domains of the genome and their function as applied to pharmacoepigenomics; (2) patient stratification from medical records; and (3) the mechanistic prediction of drug response, targets, and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence (AI) over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical, and demographic datasets.

It's one thing to track your heart rate, pulse or other movements with a smart watch or other consumer electronics, researchers say, but quite another to rely on the device to diagnose a disease. It's one thing to track your heart rate, pulse or other movements with a smart watch or other consumer electronics, researchers say, but quite another to rely on the device to diagnose a disease. With sensors that can collect data on body movements, heart rate, blood pressure and other metrics, the list of health trackers that go beyond activity trackers like Fitbits gets longer each year. "There's definitely an explosion of these things," says Dr. Joseph Kvedar, the vice president for connected health at Partners HealthCare in Boston, and an associate professor of dermatology at Harvard Medical School. Some of these devices will lead to a better health care system, Kvedar predicts, with cheaper, more efficient care.

She covers topics like artificial intelligence, augmented and virtual reality, blockchain, and big data, to name a few. Cas is also co-owner of an esports organization and spends much of her time teaching gamers how to make a living doing what they love while bringing positivity to the gaming community.

When it comes to industries that offer entrepreneurs big opportunities, they often fall into the following categories: they're highly fragmented, outdated, or just generally reviled. The industries below are, accordingly, ready for big changes. Several innovative, well-funded startups already have taken notice and are busy muscling their way in with products and services designed to change the status quo. Here are five industries--and their disruptive startups--to watch in 2018. Just about everybody needs insurance, but few people get excited about it: The health insurance industry consistently lands near the bottom of the American Customer Satisfaction Index, and life and property insurance companies aren't exactly known for their ability to inspire.

Since entrepreneur Chris Mansi cofounded Viz.ai in 2016, the best-funded wizards of artificial intelligence have taken on board games, and created emoji that mirror your facial expressions. Meanwhile, Mansi has been developing algorithms to save the brain cells of stroke patients. This month, the Food and Drug Administration cleared Viz.ai to market its algorithms to doctors and hospitals. It was a small breakthrough toward using AI to make healthcare more efficient and powerful. Someone in the US suffers a stroke every 40 seconds, according to the Centers for Disease Control.

Israel-based BrainQ is a new nuerotech startup hoping to take on brain-computer interface (BCI) companies like Braintree founder Bryan Johnson's Kernel and Silicon Valley billionaire Elon Musk's Neuralink. It's not clear yet what Musk's startup intends to do with the computer chips it plans to put in our heads but Johnson's startup says it is focused on developing "technologies to understand and treat neurological diseases in new and exciting ways." Whatever sector each company goes for, both plan to insert chips in our brains to connect us to computers -- the consequences of which could have dramatic effects on human memory, intelligence, communication and many other areas that could rocket humanity forward, should they work out. But it's early days in this industry, including for BrainQ, which plans to use a non-surgically embedded EEG machine instead to gather data and help improve outcomes for stroke and spinal cord patients. Aside from the brain implant options, BrainQ faces quite a bit of competition in this area.

Chinese device maker Lepu Medical Technology Co. has received approval from the U.S. Food and Drug Administration for the registration of an electrocardiogram analysis and diagnosis system based on artificial intelligence. The Beijing-based firm's Carewell Healthcare subsidiary developed the product, named AI ECG Platform, which covers major cardiovascular diseases, Lepu said in a statement. AI ECG Platform's diagnostic accuracy for a variety of heart diseases is over 95 percent, a similar level to ECG medical experts and it is capable of outperforming specialists for the diagnosis of some complex cases, the firm added. The company has applied for more than a dozen Chinese and international patents related to the technology. Lepu aims to promote the use of the product in primary hospitals and clinics which lack professional cardiologists.