System for diagnosis decision support by an ai assisted and optimized monitoring guidance tool, and associated method

An electronic device comprising:

• a power source;
• a communication interface configured to communicate with one or more patient monitoring devices and at least one database over a network;
• a human-machine interface configured to provide information to a user and obtain information from the user;
• a memory configured to store instructions;
• and
• at least one processor configured to execute the instructions to:
• obtain, through the communication interface, medical information corresponding to the patient from the at least one database;
• obtain, through the communication interface, real time or near real time patient monitoring data corresponding to the patient from the one or more patient monitoring devices;
• generate, by an artificial intelligence (AI) model, a differential diagnosis list for the patient based on at least one of the medical information and the patient monitoring data, the differential diagnosis list including one or more diagnoses and a predicted probability corresponding to each diagnosis, each predicted probability indicating an estimated accuracy of a corresponding diagnosis;
• provide, through the human-machine interface, the differential diagnosis list and predicted probabilities to the user;
• and
• obtain, from the user and through the human-machine interface, user predictions for one or more of the diagnoses,
• wherein the AI model includes a first neural network that is trained to generate the predicted probabilities based on previously input user predictions.

An electronic device comprising:

• a power source;
• a communication interface configured to communicate with one or more patient monitoring devices and at least one database over a network;
• a human-machine interface configured to provide information to a user and obtain information from the user;
• a memory configured to store instructions;
• and
• at least one processor configured to execute the instructions to:
• obtain, through the communication interface, medical information corresponding to the patient from the at least one database;
• obtain, through the communication interface, real time or near real time patient monitoring data corresponding to the patient from the one or more patient monitoring devices;
• generate, by an artificial intelligence (AI) model;
• a differential diagnosis list for the patient based on at least one of the medical information and the patient monitoring data, the differential diagnosis list including one or more diagnoses;
• a predicted probability corresponding to each diagnosis, each predicted probability indicating an estimated accuracy of a corresponding diagnosis;
• one or more recommendations for a first diagnosis of the differential diagnosis list;
• and
• a recommendation weight for each of the one or more recommendations, the recommendation weight indicating a change in a predicted probability of a diagnosis based on the information corresponding to the recommendation being considered in the corresponding diagnosis;
• and
• provide, through the human-machine interface, the differential diagnosis list, the predicted probabilities, the one or more recommendations, and the one or more recommendation weights to the user;
• wherein the one or more recommendations comprise one of an additional parameter to be monitored, a diagnostic test to be performed, and an imaging study to be performed