How Hospitals Are Using AI to Save Lives

Artificial-intelligence algorithms are processing vast troves of data in electronic medical records, searching for patterns to predict future outcomes and recommend treatments. They are creating early-warning systems to help hospital staff spot subtle but serious changes in a patient's condition that aren't always visible or noticed in a busy unit, and predicting which patients about to be discharged from the hospital are at highest risk of being readmitted. These systems are just one effort in a vast array of AI projects in healthcare--from helping detect cancer in radiology images to identifying which drugs to test on patients with different diseases. But this prediction technology holds especially significant promise to transform care and improve patient safety in ER and ICU cases--as long as the systems can be designed to avoid some of the medical, technological and ethical concerns that have emerged in mixing the science of machine learning with the art of medicine. Sepsis Watch is based on data from 42,000 inpatient encounters, with 21.3% of those patients having experienced sepsis.