Recently we talked before how big data is the new frontier with just .05% of all data available today having been analyzed. This means that all kinds of gold prospectors are lining up with their freshly crafted artificial intelligence (AI) algorithms looking to extract all the value they can from this wild west of data before someone else does. Perhaps nowhere is there more excitement at the moment than the applications to be had in the healthcare industry. Here's a look at just some of the startups that are applying artificial intelligence and big data to healthcare (courtesy of the bright minds over at CB Insights): The application that we've circled above is "drug discovery" using AI or what's also known as "computational drug discovery". The reason that this is now a thing is not just because of all the big data that's available now, but also because of how cheap cloud computing has become, not to mention the emergence of deep learning algorithms.

There are many choices we make over the course of our lives. Some are fairly insignificant, like the clothes we put on in the morning; others, such as the vocations we settle on, have life-changing consequences. But there's one critical decision we don't get to make: the choice of being born into a human body--and all the arbitrary ailments and inevitable biological breakdowns that follow. This is what sets health care apart from other industries. The business of medicine is quite literally one of life and death. And throughout much of the world, it remains a messy, inefficient, expensive sector in need of radical reform. Just consider some of the heart-wrenching numbers.

By the way, you can listen to a neuron fire here (what you're actually hearing is the electro-chemical firing of a neuron, converted to audio). Some electrodes want to take the relationship to the next level and will go for a technique called the patch clamp, whereby it'll get rid of its electrode tip, leaving just a tiny little tube called a glass pipette,21 and it'll actually directly assault a neuron by sucking a "patch" of its membrane into the tube, allowing for even finer measurements:39 A patch clamp also has the benefit that, unlike all the other methods we've discussed, because it's physically touching the neuron, it can not only record but stimulate the neuron,22 injecting current or holding voltage at a set level to do specific tests (other methods can stimulate neurons, but only entire groups together). Finally, electrodes can fully defile the neuron and actually penetrate through the membrane, which is called sharp electrode recording. If the tip is sharp enough, this won't destroy the cell--the membrane will actually seal around the electrode, making it very easy to stimulate the neuron or record the voltage difference between the inside and outside of the neuron. But this is a short-term technique--a punctured neuron won't survive long.

Existing VR systems and experiences are immersive, engaging and sometimes even interactive. But they don't offer a quick, easy way for you to express your emotions. Medical device maker MindMaze has come up with a novel, compelling way to convey your facial expressions in VR called Mask. It's a foam insert that's compatible with existing headsets and uses diodes to read your biosignals and muscles. The potential applications here are plenty: You could deduce, from your opponents' faces, when they're preparing to shoot or see a new acquaintance laugh at your joke in social VR scenarios.

Developing new drugs is notoriously inefficient. Fewer than 12 percent of all drugs entering clinical trials end up in pharmacies, and it costs about $2.6 billion to bring a drug to market. There are so many molecules to test that pharmaceutical researchers use pipetting robots to test a few thousand variants all at once. The best candidates then go into animal models or cell cultures, where hopefully a few will go on to bigger animal and human clinical trials. Which is why more and more drug developers are turning to computers and artificial intelligence to narrow down the list of potential drug molecules--saving time and money on those downstream tests.

Deep learning has been used to transform artificial intelligence (AI) development, whether it is from beating players in games like Go or poker to improving self-driving AI. But perhaps the most important changes for most of us is how AI advances and machine learning are affecting healthcare. In January, a medical startup won FDA approval for an AI-assisted cardiac imaging system called Arterys, and AI is playing vital roles in other health fields such as fighting cancer and aging. NVIDIA boasts that with deep learning, "AI can help doctors make faster, more accurate diagnoses. It can predict the risk of a disease in time to prevent it."

The world knows no deadlier assassin than heart disease. It accounts for one in four fatalities in the US. Early detection remains the key to saving lives, but catching problems at the right time too often relies upon dumb luck. The most effective way of identifying problems involves an EKG machine, a bulky device with electrodes and wires. Even many portable machines like battery-powered Holter monitors, are unwieldy.

Artificial intelligence (AI) is steadily reshaping healthcare from all sides, introducing technologies we wouldn't have thought possible five or 10 years ago. It's happening in the clinic (see HealthTap's Doctor A.I.), it's happening in diagnostics (see IBM Watson), and now it's moving into earlier-stage drug discovery with Palo Alto, California-based twoXAR. "In the couple years that we have been around, we've been told hundreds of times that computers cannot do this; that biology is too complex; that this will never work," said Andrew A. Radin, CEO of the AI-driven biopharmaceutical company. "Yet, in every single disease program where we have run proof-of-concept studies on our novel AI-identified candidates, we have generated efficacious results across standard end points." Using a custom-built computational platform, twoXAR works to identify what it calls "unanticipated associations between drug and disease."

AliveCor, which has developed an FDA-cleared smartphone-enabled ECG device, has launched a clinician-facing app using artificial intelligence to pick up signs of atrial fibrillation earlier, according to a company news release. It's an interesting development for the business because it can alert physicians to patients with an elevated risk of having a stroke. The Kardia Pro app is for clinical use. But the goal is to analyze data from patients that includes weight, activity and blood pressure with AI to personalize the heart profiles of each patient, the news release said. An estimated 795,000 people suffer a stroke each year, the majority of them for the first time.

Technically it ain't brain surgery, but let's just say you wouldn't want to do a cochlear implant while sleepy or distracted. So it's a good thing this surgery robot can't be either of those things. The bit passes just half a millimeter from the facial nerve, and another half a millimeter from the taste nerve, before entering the spiraling cochlea of the inner ear. The first robot-assisted cochlear implant in a clinical trial, which researchers describe today in the journal Science Robotics, doesn't just enhance a surgeon's dexterity like the by-now-common da Vinci robot might. "We are interested in doing something with the robot that a surgeon is not able to do," says study co-author Stefan Weber of the ARTORG Center for Biomedical Engineering Research.