PATTERN RECOGNITION SYSTEM FOR QUANTIFYING THE LIKELIHOOD OF THE CONTRIBUTION OF MULTIPLE POSSIBLE FORMS OF CHRONIC DISEASE TO PATIENT REPORTED DYSPNEA
ANDERSON STEPHEN T,MACCARTER DEAN J,ANDERSON DAVID M
申请号：
IN201637036532
公开号：
IN201637036532A
申请日:
2016.10.25
申请国别(地区):
IN
年份:
2016
代理人:
摘要：
Systems and methods for quantifying the likelihood of the contribution of multiple possible forms of chronic disease to patient reported dyspnea can include the testing protocol having a flow/volume loop performed at rest flowed by the measurement of cardiopulmonary exercise gas exchange variables during rest exercise and recovery as unique data sets. The data sets are analyzed using feature extraction steps to produce a pictorial image consisting of disease silos displaying the likelihood of the contribution of various chronic diseases to patient reported dyspnea. In some embodiments the silos are split into subclass silos. In some embodiments multiple chronic disease indexes are used to differentiate between sub types of a particular chronic disease (e.g. differentiating WHO 1 PH from WHO 2 or WHO 3 PH). Test results are plotted serially to asses to provide feedback to the physician on the efficacy of therapy provided to the patient.
