System, method, and computer-accessible medium for point processes for competing observations with recurrent networks

A method for predicting medical events used for a treatment of at least particular one of a plurality of patients, comprising:

• receiving first medical information for each of the patients, wherein the medical information includes at least one of the medical events and a time associated with the at least one of the medical events;
• generating a summary of the medical information;
• generating a multivariate point process model based on the summarized medical information, wherein each of the medical events has its own distinct sub-model which tracks progression of interevent times for that particular medical event;
• receiving second medical information for the at least particular one of the patients;
• and
• predicting and facilitating at least possible one of the medical events and a predicted time of the at least possible one of the medical events for the at least particular one of the patients.

A non-transitory computer-accessible medium having stored thereon computer-executable instructions for determining phenotypic information for a treatment of at least particular one of a plurality of patients, the computing arrangement is configured to perform procedures comprising:

• receiving first medical information for each of the patients, wherein the medical information includes at least one of the medical events and a time associated with the at least one of the medical events;
• generating a summary of the medical information;
• generating a multivariate point process model based on the summarized medical information, wherein a computation of a non-estimated probability distribution is used to train the multivariate point process model;
• receiving second medical information for the at least particular one of the patients;
• and
• predicting and facilitating at least possible one of the medical events and a predicted time of the at least possible one of the medical events for the at least particular one of the patients.

A non-transitory computer-accessible medium having stored thereon computer-executable instructions for determining phenotypic information for a treatment of at least particular one of a plurality of patients, the computing arrangement is configured to perform procedures comprising:

• receiving first medical information for each of the patients, wherein the medical information includes at least one of the medical events and a time associated with the at least one of the medical events;
• generating a summary of the medical information;
• generating a multivariate point process model based on the summarized medical information, wherein each of the medical events has its own distinct sub-model which tracks progression of interevent times for that particular medical event;
• receiving second medical information for the at least particular one of the patients;
• and
• predicting and facilitating at least possible one of the medical events and a predicted time of the at least possible one of the medical events for the at least particular one of the patients.

A system for predicting medical events used for a treatment of at least particular one of a plurality of patients, comprising:

• a computer hardware arrangement configured to:
• receive first medical information for each of the patients, wherein the medical information includes at least one of the medical events and a time associated with the at least one of the medical events;
• generate a summary of the medical information;
• generate a multivariate point process model based on the summarized medical information, wherein a computation of a non-estimated probability distribution is used to train the multivariate point process model;
• receive second medical information for the at least particular one of the patients;
• and
• predict and facilitate at least possible one of the medical events and a predicted time of the at least possible one of the medical events for the at least particular one of the patients.

A system for predicting medical events used for a treatment of at least particular one of a plurality of patients, comprising:

• a computer hardware arrangement configured to:
• receive first medical information for each of the patients, wherein the medical information includes at least one of the medical events and a time associated with the at least one of the medical events;
• generate a summary of the medical information;
• generate a multivariate point process model based on the summarized medical information, wherein each of the medical events has its own distinct sub-model which tracks progression of interevent times for that particular medical event;
• receive second medical information for the at least particular one of the patients;
• and
• predict and facilitate at least possible one of the medical events and a predicted time of the at least possible one of the medical events for the at least particular one of the patients.