AI Cardiologist Aces Its First Medical Exam

A neural network outperforms human cardiologists in a task involving heart scans Photo-illustration: Rima Arnaout Rima Arnaout wants to be clear: The AI she created to analyze heart scans, which easily outperformed human experts on its task, is not ready to replace cardiologists.  It was a limited task, she notes, just the first step in what a cardiologist does when evaluating an echocardiogram (the image produced by bouncing sound waves off the heart). “The best technique is still inside the head of the trained echocardiographer,” she says. But with experimental artificial intelligence systems making such rapid progress in the medical realm, particularly on tasks involving medical images, Arnaout does see the potential for big changes in her profession. And when her 10-year-old cousin expressed the desire to be a radiologist when she grows up, Arnaout had some clear advice: “I told her that she should learn to code,” she says Continue reading AI Cardiologist Aces Its First Medical Exam

Cracking Open the Black Box of AI with Cell Biology

A deep neural network that’s mapped to the innards of a yeast cell reveals its inner workings Image: iStock Phot The deep neural networks that power today’s artificial intelligence systems work in mysterious ways. They’re black boxes: A question goes in (“Is this a photo of a cat?” “What’s the best next move in this game of Go?” “Should this self-driving car accelerate at this yellow light?”), and an answer comes out the other side. We may not know exactly how a black box AI system works, but we know that it does work. But a new study that mapped a neural network to the components within a simple yeast cell allowed researchers to watch the AI system at work. And it gave them insights into cell biology in the process. The resulting tech could help in the quest for new cancer drugs and personalized treatments.  First, let’s cover the basics Continue reading Cracking Open the Black Box of AI with Cell Biology

Stanford’s AI Predicts Death for Better End-of-Life Care

Deep learning AI is helping screen for ill patients who could benefit from having end-of-life conversations earlier Illustration: iStockphoto Using artificial intelligence to predict when patients may die sounds like an episode from the dystopian science fiction TV series “Black Mirror.” But Stanford University researchers see this use of AI as a benign opportunity to help prompt physicians and patients to have necessary end-of-life conversations earlier. Many physicians often provide overly rosy estimates about when their patients will die and delay having the difficult conversations about end-of-life options. That understandable human tendency can lead to patients receiving unwanted, expensive and aggressive treatments in a hospital at their time of death instead of being allowed to die more peacefully in relative comfort. The alternative being tested by a Stanford University team would use AI to help physicians screen for newly-admitted patients who could benefit from talking about palliative care choices. Past studies have shown that about 80 percent of Americans would prefer Continue reading Stanford’s AI Predicts Death for Better End-of-Life Care

Stanford Algorithm Can Diagnose Pneumonia Better Than Radiologists

It took Stanford AI researchers just a month to beat radiologists at the pneumonia game Photo: Stanford Stanford researchers have developed a machine-learning algorithm that can diagnose pneumonia from a chest x-ray better than a human radiologist can. And it learned how to do so in just about a month. The Machine Learning Group, led by Stanford adjunct professor Andrew Ng, was inspired by a data set released by the National Institutes of Health on 26 September. The data set contains 112,120 chest X-ray images labeled with 14 different possible diagnoses, along with some preliminary algorithms. The researchers asked four Stanford radiologists to annotate 420 of the images for possible indications of pneumonia. They selected that disease because, according to a press release, it is particularly hard to spot on X-rays, and brings 1 million people to U.S. hospitals each year. Within a week, the Stanford team had developed an algorithm, Continue reading Stanford Algorithm Can Diagnose Pneumonia Better Than Radiologists

Cincinnati Schools Roll Out Tech to Identify Teens Likely to Attempt Suicide

An app uses deep learning to flag word choice and vocal patterns linked to suicide risk Photo: Alexander Trinitatov/Getty Images At 10 public schools in Cincinnati, middle and high school students will have a new app looking out for them this year. When a student from those schools goes to the health clinic for a talk with the staff psychologist, an iPhone app will listen to the conversation and flag those students it considers likely to attempt suicide. There’s a dire need for tech that can detect young people who need help. Suicide is the second-leading cause of death for people ages 15 to 24, surpassed only by accidents. The tech, which has been tested in the Cincinnati schools during the past two years, comes from John Pestian, director of the computational medicine lab at Cincinnati Children’s Hospital. “The school psychologist just turns on the app as they’re talking to Continue reading Cincinnati Schools Roll Out Tech to Identify Teens Likely to Attempt Suicide