Sequence mining in medical IoT data

A computer-implemented method for maintenance of a medical imaging device, the method comprising:

• providing at least one training log file including a list of events, each of the at least one training log file corresponding to at least one medical imaging device, and each event in the list of events including at least a unique identifier and a timestamp;
• applying a SPADE algorithm to the at least one training log file to determine, as a configuration dataset, a sub-set including sequences of events that fulfill a finishing criterion;
• configuring a computing device to recognize a sequence of events, in the configuration dataset as indicative of a failure of the medical imaging device, in an event sequence list provided to the computing device;
• providing at least a first event sequence list to the computing device, the first event sequence list including a first list of events, and the first event sequence list corresponding to the medical imaging device;
• predicting, using the computing device, a failure of the medical imaging device based on the first event sequence list;
• and
• at least one of (i) automatically scheduling maintenance of the medical imaging device or (ii) rescheduling or re-tasking at least one function of the medical imaging device, in response to predicting the failure of the medical imaging device, wherein
• the re-tasking re-tasks the at least one function of the medical imaging device to a different medical imaging device, and
• within the SPADE algorithm, each sub-set of events for a same medical imaging device is considered to be a sequence, or part of a sequence, when an absolute value of a difference between a first event timestamp and a second event timestamp, of the sequence of events, is less than a defined backward gap value, and when an absolute value of a difference between a third event timestamp and the first event timestamp, of the sequence of events, is less than a defined forward gap value.