Diagnosed by a Machine: Artificial Intelligence Takes Over from Doctors

On May 12, Politico published some frightening statistics about when “not to get sick,” largely based on hospital statistics and interviews with nurses.

Every July in U.S.-based teaching hospitals, medical students become interns, interns become residents, and each level of resident moves up a level.

The National Bureau of Economic Research summed this up nicely: “On day one, new interns have the same responsibilities that the now second-year residents had at the end of June” (i.e. one year).

This creates what health care workers call “The July effect” in the United States and “August Killing Season” in the United Kingdom.

As inexperienced physicians take patients’ lives into their hands, the changeover results in harmful patient care, increased medical errors, improper medication, and longer hospital stays.

Just in July, these hospitals see a surge in death rates between 8% and 34%. That’s a total of between 1,500 and 2,750 deaths.

In Britain, August mortality rates rise between 6% and 8% for the same reasons.

Analysis of the data could reduce this problem by leveraging algorithms with artificial intelligence, with tech giants such as Apple, Google, and Microsoft giving a major hand with their consumer products and massive computing infrastructure.

Doctors are now able to log on to collective intelligence systems such as “Modernizing Medicine,” which provides web-based, data driven insights from over 3,700 health care providers servicing 14 million patients.

Ever buy a product from Amazon or order a movie from Netflix? The same kind of technology used to recommend similar items to buy or movies to watch is now helping doctors recommend treatments for complex diseases.

Every day these systems are getting “smarter” by taking data from digital medical records, genetics, textbooks, journals, and even the devices we carry every day.

These systems then alert doctors to possible trends buried deep in the data, which are typically missed by new and sometimes even experienced physicians. They can then deliver customized medical care that offers the statistically highest likelihood of success, with the lowest risk of side effects.

It’s these sort of innovations in the medical field that I’m tracking for my BioTech Intel Trader subscribers, as we hunt for profitable opportunities sweeping the industry by storm.

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About Author

Ben Benoy is a veteran of the U.S. Marine Corps and has been an active retail trader since 2006. He identifies investment opportunities based on key social media trends. He first identified the concept in 2008 and has since developed a tool for tracking investment “chatter” between social media users. His proprietary Social Media Stock Sentiment system has developed into a state-of-the-art platform that identifies and classifies chatter about stocks through algorithms and other indicators to forecast stock-price direction. Ben’s track record speaks for itself — over the past 12 months, his system boasts a win rate of 82.2% on 112 stock trades.