Skip to Content
Artificial intelligence

Blood infections kill millions—but AI could help

October 23, 2018

Sepsis is a potentially life-threatening complication of a bacterial infection—it kills one in five of the 30 million people who contract it worldwide every year. But a new study in Nature suggests a system built using reinforcement learning could significantly reduce that number.

What is reinforcement learning? It’s a machine-learning technique inspired by the way animals learn through positive feedback. It’s the same technique DeepMind used to create a program that taught itself to play Go.

The research: This method was used by a team from Imperial College London who fed a system data on the way 96,156 sepsis patients admitted to 133 separate intensive care units in the US had been treated. The data included information on medication doses, intravenous fluids, and vasopressors (medicines that constrict blood vessels) given over the first 72 hours after admission to hospital. The system’s end goal was patient survival after 90 days.

Better outcomes: It’s yet to be tested in hospitals, but when compared with an independent validation sample, the program was significantly better at recommending sepsis treatment than human doctors, the team found.

AI assistant: The software is yet another in a growing cadre of AI-powered systems aimed at helping doctors treat tough diseases, especially when it comes to diagnosis. For example, Google’s deep-learning tool recently proved better than human pathologists at spotting metastatic tumors. A number of new apps also use AI techniques to help triage patients. 

Deep Dive

Artificial intelligence

A Roomba recorded a woman on the toilet. How did screenshots end up on Facebook?

Robot vacuum companies say your images are safe, but a sprawling global supply chain for data from our devices creates risk.

The viral AI avatar app Lensa undressed me—without my consent

My avatars were cartoonishly pornified, while my male colleagues got to be astronauts, explorers, and inventors.

Roomba testers feel misled after intimate images ended up on Facebook

An MIT Technology Review investigation recently revealed how images of a minor and a tester on the toilet ended up on social media. iRobot said it had consent to collect this kind of data from inside homes—but participants say otherwise.

How to spot AI-generated text

The internet is increasingly awash with text written by AI software. We need new tools to detect it.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.