Method and system for predicting continous cardiac output (cco) of a patient based on physiological data

Abstract

The various embodiments of the present invention disclose a method and system for predicting a physiological condition of a patient during post-surgery recovery in Intensive Care Unit (ICU). The physiological condition is the Continuous Cardiac Output (CCO) of a patient ahead of time based on past physiological data. The method comprises of developing a clinical database containing a clinical data captured from a plurality of historical patients having similar patient profiles, the clinical data comprising physiological data, vital signs, demographic details, pretreatment symptoms, and treatments, of historical patients, identifying recovery patterns for the similar patient profiles which exhibits likewise response to a selected treatment regime, utilizing the recovery patterns for learning the behavioral response of a physiological parameter of a patient and creating a prediction model to enable automated classification of similar patient profiles from existing recovery patterns of known symptoms and known responses to at least one treatment regime.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of U.S. Provisional Patent Application: 62061970, entitled "Method and System for Predicting Continuous Cardiac Output (CCO) in a Patient Based on Physiological Data," filed October 9, 2014, the entire contents of which are incorporated by reference Incorporated herein for all purposes. technical field [0003] The present disclosure relates generally to patient monitoring systems and methods, and more particularly to methods and systems for continuously monitoring cardiac parameters of a patient to predict continuous cardiac output (CCO). Background technique [0004] Patient outcomes during recovery rely on monitoring and analysis of various physiological data collected over time to allow for early analysis and identification of potential problems. Especially in intensive care units, this data becomes invaluable, requiring continuous monitoring of patient vital signs in order to p...

AI Technical Summary

Problems solved by technology

However, a significant disadvantage of this method is its inaccuracy and inability to predict into the future, since these models are simple empirical formulas made of relevant factors and assumptions that are insufficient for accurate prediction

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