AI decision support algorithm for mass-casualty events under development

Omer Perry, a lecturer in the School of Industrial Engineering & Management at Afeka College of Engineering in Tel Aviv, has spent the last six years studying how stressful mass casualty events affect the cognitive ability of EMTs and paramedics, and, in the last year, he and his team have been working extensively to develop an AI-based algorithm that could help paramedics improve decision-making during high-stress casualty events. Perry has found that during this type of event, people meet the edge of their human capacity, but through the recognition of human limitations, he was able to develop an algorithm to help minimize the amount of information that a paramedic takes in by scanning the data on the casualties at the scene and setting the order of their treatment and evacuation. The ultimate goal is to minimize the deterioration of patients at the scene. Perry and his team are now working to optimize the algorithm’s decision-making process and expect it to be available for use in approximately a year’s time.