How Artificial Intelligence will Revolutionize Healthcare

Diagnosis, treatment, research, patient compliance, and follow-up—all of these are going to be revolutionized by artificial intelligence (AI). Better treatment options and outcomes, and better results are on the way, but challenges remain. 


Robot that looks human.

In 2013 Jeopardy! fans were blown away as IBM’s supercomputer WATSON wiped the floor with longtime champion Ken Jennings. Now WATSON HEALTH AI is being used in 16 cancer institutes across the country, helping to diagnose and treat patients. Meanwhile Google, not to be outdone, has launched DeepMind, which recently earned the title world champion of the complex game of Go. Now, DeepMind Health will create innovative new apps for healthcare professionals alerting them to patient emergencies, and the risk of complications when considering possible treatment options. Progenitors say that someday, it should even be able to predict a patient’s needs down the pike.  


Other tech companies such as Dell, Hewlett-Packard, Apple, and Hitachi are also putting together AI programs for the healthcare field. Within the next five years, AI’s use in medicine is expected to increase tenfold. There are several areas where it is predicted to revolutionize healthcare, and places where it is already in use. In some cases, these advanced algorithms—all that AI is, has been proven to diagnose disease faster than humans.

Picture it, a patient comes in with terrible symptoms. The physician, a well-seasoned professional, has never seen anything like it before. In years gone by, in-depth research would take time, perhaps time the patient didn’t have. Today, a physician can log into Modernizing Medicine, find what rare condition it is, scroll through the treatment options available, and write a prescription in mere seconds. AI can help diagnose illness, offer novel treatment options, eliminate human error, and take care of all the repetitive tasks that clog up the system. These time saving measures mean more efficiency and reduced costs.

The healthcare-related information we possess today is astronomical. AI can help us sort through it. Modernizing Medicine collates data from 3,700 providers and over 14 million patient visits. Though impressive, future capabilities will dwarf this feat. IBM recently purchased Merge Healthcare Inc., a company with a repository of 30 billion medical images of every sort, which will be used to train WATSON to diagnose disease.


AI can also prevent recidivism, by helping follow cases and make further recommendations as time rolls on. At Vanderbilt University Medical Center and St. Jude’s Medical Center, both in Tennessee, electronic medical records are imbued with AI. A physician using them will occasionally get a pop-up explaining how certain genetic traits might affect their patient’s illness or how a new drug could improve their condition. Just by clicking the pop-up, a doctor can learn more, even prescribe a different medication. These e-medical records aren’t just saving time and space, they are actively helping to make patients better and doctors aware of the options and nuances before them. Some see applications in biomedicine too, personalizing treatment. Theoretically, AI can take a person’s genome and recommend treatment options that will serve them best, while limiting or even eliminating side effects.

In research, AI can streamline the selection process of drug development to be sure investigators are studying those which show the most promise, and help identify previously undiscovered pathways that could lead to new treatments and therapies. Treatment is one thing, compliance another. That’s why AICure contacts patients to ensure they are taking their medicine and doing so properly, helping patients manage their own treatment and care.

AI is expected to be a helpful tool. Rather than replace doctors, it should advance their capabilities and cover blind spots. That is, if we get the I, Robot future rather than the Terminator hellscape—as Stephen Hawking and others have warned. Chances are, it will be a mix of both, and far less dramatic. Though these technologies promise much, dovetailing them into our current healthcare system and training doctors and other medical professionals to use them remains a challenge. Also, as AI advances, we are bound to have a few hiccups along the way.

To learn more about WATSON click here: 

Massive 'Darth Vader' isopod found lurking in the Indian Ocean

The father of all giant sea bugs was recently discovered off the coast of Java.

A close up of Bathynomus raksasa

SJADE 2018
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  • A new species of isopod with a resemblance to a certain Sith lord was just discovered.
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Astronomers find more than 100,000 "stellar nurseries"

Every star we can see, including our sun, was born in one of these violent clouds.

Credit: NASA / ESA via Getty Images
Surprising Science

This article was originally published on our sister site, Freethink.

An international team of astronomers has conducted the biggest survey of stellar nurseries to date, charting more than 100,000 star-birthing regions across our corner of the universe.

Stellar nurseries: Outer space is filled with clouds of dust and gas called nebulae. In some of these nebulae, gravity will pull the dust and gas into clumps that eventually get so big, they collapse on themselves — and a star is born.

These star-birthing nebulae are known as stellar nurseries.

The challenge: Stars are a key part of the universe — they lead to the formation of planets and produce the elements needed to create life as we know it. A better understanding of stars, then, means a better understanding of the universe — but there's still a lot we don't know about star formation.

This is partly because it's hard to see what's going on in stellar nurseries — the clouds of dust obscure optical telescopes' view — and also because there are just so many of them that it's hard to know what the average nursery is like.

The survey: The astronomers conducted their survey of stellar nurseries using the massive ALMA telescope array in Chile. Because ALMA is a radio telescope, it captures the radio waves emanating from celestial objects, rather than the light.

"The new thing ... is that we can use ALMA to take pictures of many galaxies, and these pictures are as sharp and detailed as those taken by optical telescopes," Jiayi Sun, an Ohio State University (OSU) researcher, said in a press release.

"This just hasn't been possible before."

Over the course of the five-year survey, the group was able to chart more than 100,000 stellar nurseries across more than 90 nearby galaxies, expanding the amount of available data on the celestial objects tenfold, according to OSU researcher Adam Leroy.

New insights: The survey is already yielding new insights into stellar nurseries, including the fact that they appear to be more diverse than previously thought.

"For a long time, conventional wisdom among astronomers was that all stellar nurseries looked more or less the same," Sun said. "But with this survey we can see that this is really not the case."

"While there are some similarities, the nature and appearance of these nurseries change within and among galaxies," he continued, "just like cities or trees may vary in important ways as you go from place to place across the world."

Astronomers have also learned from the survey that stellar nurseries aren't particularly efficient at producing stars and tend to live for only 10 to 30 million years, which isn't very long on a universal scale.

Looking ahead: Data from the survey is now publicly available, so expect to see other researchers using it to make their own observations about stellar nurseries in the future.

"We have an incredible dataset here that will continue to be useful," Leroy said. "This is really a new view of galaxies and we expect to be learning from it for years to come."

Protecting space stations from deadly space debris

Tiny specks of space debris can move faster than bullets and cause way more damage. Cleaning it up is imperative.

  • NASA estimates that more than 500,000 pieces of space trash larger than a marble are currently in orbit. Estimates exceed 128 million pieces when factoring in smaller pieces from collisions. At 17,500 MPH, even a paint chip can cause serious damage.
  • To prevent this untrackable space debris from taking out satellites and putting astronauts in danger, scientists have been working on ways to retrieve large objects before they collide and create more problems.
  • The team at Clearspace, in collaboration with the European Space Agency, is on a mission to capture one such object using an autonomous spacecraft with claw-like arms. It's an expensive and very tricky mission, but one that could have a major impact on the future of space exploration.

This is the first episode of Just Might Work, an original series by Freethink, focused on surprising solutions to our biggest problems.

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