Nippon Telegraph and Telephone Corporation

Sunyong Kim

Ippei Shake

Atsuhiko Maeda

Kazuaki Obana

Yukio Kikuya

Michiharu Takemoto

Kenichi Fukuda

Tetsuo Kawano

Hiroshi Sato

Provided is a technique for efficiently predicting the number (quantity) of occurrences of emergency medical service requests in a target area. An emergency medical service demand prediction device according to an embodiment obtains actual history data including information about dates and times of occurrences of emergency medical service requests, information about positions of the occurrences of the emergency medical service requests, and information about illnesses and injuries that caused the emergency medical service requests; the device generates a first learning model that receives an input of first learning-purpose data generated on a basis of learning-purpose actual history data and outputs illness/injury groups; the device generates a second learning model that receives an input of second learning-purpose data generated on a basis of the learning-purpose actual history data and the illness/injury groups output from the first learning model and outputs a value indicating a quantity of occurrences of emergency medical service requests for each unit area; and the device predicts a quantity of occurrences of emergency medical service requests in each unit area, by inputting, to the second learning model having been trained, prediction-purpose data generated on a basis of prediction-purpose actual history data and the illness/injury groups output from the first learning model having been trained.

Emergency demand prediction device, emergency demand prediction method, and program

Growing community of inventors

Musashino, Japan

Sunyong Kim