Method and system using artificial intelligence to monitor user characteristics during a telemedicine session

A method comprising:

• receiving treatment data pertaining to a user who uses a treatment device to perform a treatment plan, wherein the treatment data comprises at least one of characteristics of the user, baseline measurement information pertaining to the user, measurement information pertaining to the user while the user performs the treatment plan, characteristics of the treatment device, and at least one aspect of the treatment plan;
• writing to an associated memory, for access by an artificial intelligence engine, the treatment data, the artificial intelligence engine being configured to use at least one machine learning model that uses at least one aspect of the treatment data to generate at least one prediction;
• receiving, from the artificial intelligence engine, the at least one prediction;
• identifying a threshold corresponding to the at least one prediction;
• in response to a determination that the at least one prediction is within a range of the threshold, communicating with an interface, at a computing device of a healthcare provider, the at least one prediction and the treatment data;
• and
• in response to a determination that the at least one prediction is outside of the range of the threshold, updating the treatment data pertaining to the user to indicate the at least one prediction.

A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:

• receive treatment data pertaining to a user who uses a treatment device to perform a treatment plan, wherein the treatment data comprises at least one of characteristics of the user, baseline measurement information pertaining to the user, measurement information pertaining to the user while the user performs the treatment plan, characteristics of the treatment device, and at least one aspect of the treatment plan;
• write to an associated memory, for access by an artificial intelligence engine, the treatment data, the artificial intelligence engine being configured to use at least one machine learning model that uses at least one aspect of the treatment data to generate at least one prediction;
• receive, from the artificial intelligence engine, the at least one prediction;
• identify a threshold corresponding to the at least one prediction;
• in response to a determination that the at least one prediction is within a range of the threshold, communicate with an interface, at a computing device of a healthcare provider, to provide the at least one prediction and the treatment data;
• and
• in response to a determination that the at least one prediction is outside of the range of the threshold, update the treatment data pertaining to the user to indicate the at least one prediction.

A system comprising:

• a processing device;
• and
• a memory including instructions that, when executed by the processor, cause the processor to:
• receive treatment data pertaining to a user who uses a treatment device to perform a treatment plan, wherein the treatment data comprises at least one of characteristics of the user, baseline measurement information pertaining to the user, measurement information pertaining to the user while the user performs the treatment plan, characteristics of the treatment device, and at least one aspect of the treatment plan;
• write to an associated memory, for access by an artificial intelligence engine, the treatment data, the artificial intelligence engine being configured to use at least one machine learning model that uses at least one aspect of the treatment data to generate at least one prediction;
• receive, from the artificial intelligence engine, the at least one prediction;
• identify a threshold corresponding to the at least one prediction;
• in response to a determination that the at least one prediction is within a range of the threshold, communicate with an interface, at a computing device of a healthcare provider, to provide the at least one prediction and the treatment data;
• and
• in response to a determination that the at least one prediction is outside of the range of the threshold, update the treatment data pertaining to the user to indicate the at least one prediction.