“Deep learning” AI system trounced doctors in predicting heart failure in patients, boasting 97 percent accuracy

Autonomous cars are controversial, but proponents point out that they are far safer than traditional cars because the artificial intelligence systems controlling them are not vulnerable to human error. The computer, they say, won’t fall asleep at the wheel, get distracted checking its text messages, or drive while intoxicated. It’s better at math than humans, accurately calculating when to slow down or change lanes safely. Now this same technology could bring new levels of accuracy to the medical field and even save lives.

Deep learning computers developed by Case Western Reserve University have been handily outperforming medical doctors in detecting cancer and diagnosing heart failure. With $9.5 million in funding from the National Cancer Institute, they’ve developed tools that can analyze digital pathology images of cancers of the lung, head, neck and breast to accurately identify those patients who could be spared undergoing risky chemotherapy.

For example, the researchers have found that their system is better than human experts in distinguishing malignant and benign lung nodules using CAT scans. This is a very valuable advancement when you consider the fact that around 98 percent of the nodules flagged by human radiologists as being suspicious turn out to be benign. The system could save people a lot of worry, not to mention unnecessary additional testing.