Systems and methods for treating heart failure with preserved ejection fraction

A computer-implemented method, the computer implemented method comprising:

• executing, by one or more processors, a feedforward artificial intelligence, the executing the machine learning algorithm comprising:
• receiving, by one or more processors, a plurality of patient parameters, the plurality of patient parameters comprising:
• one or more patients having diastolic dysfunction and one or more patients not having diastolic dysfunction,
• one or more patients having cardiac fibrosis and one or more patients not having cardiac fibrosis,
• one or more patients having pulmonary hypertension and one or more patients not having pulmonary hypertension,
• one or more patients having a left ventricular ejection fraction of ≥50%, and one or more patients not having a left ventricular ejection fraction of ≥50%,
• and
• one or more patients having cardiac amyloid deposits and one or more patients not having cardiac amyloid deposits,
• analyzing, by one or more processors, the plurality of patient parameters,
• arranging, by one or more processors, the plurality of patient parameters into neurons of an input layer of an artificial neural network,
• applying, by one or more processors, a weight to the plurality of patient parameters arranged in the input layer,
• arranging, by one or more processors, the weighted plurality of patient parameters to one or more hidden layers of the feedforward artificial neural network, and
• generating, by one or more processors, a plurality of optimized data sets of patient parameters;
• executing, by one or more processors, a cluster analysis, the executing comprising:
• receiving, by one or more processors, a plurality of optimized data sets of patient parameters,
• wherein the plurality of optimized data sets of patient parameters includes data of a plurality of patients;
• analyzing, by one or more processors, the plurality of optimized data sets of patient parameters,
• identifying, by one or more processors, a plurality of populations among the plurality of optimized data sets of patient parameters, and
• generating, by one or more processors, one or more clusters of the plurality of populations,
• analyzing, by one or more processors, the one or more clusters of the plurality of populations generated by the cluster analysis, and
• generating, by one or more processors, a set of instructions to administer an effective amount of a Rho-kinase inhibitor, an anti-fibrosis compound, or a pharmaceutically acceptable salt, ester, or solvate thereof, to a subject experiencing:
• diastolic dysfunction,
• cardiac fibrosis,
• pulmonary hypertension, and
• a left ventricular ejection fraction of ≥50%,
• wherein the subject does not have cardiac amyloid deposits, and
• administering to the subject a therapeutically effective amount of the Rho-kinase inhibitor, the anti-fibrosis compound, or the pharmaceutically acceptable salt, ester or solvate thereof.

A method of reducing the stiffness of heart tissue, the method comprising:

• administering a therapeutically effective amount of a Rho-kinase inhibitor, an anti-fibrosis compound, or a pharmaceutically acceptable salt, ester, or solvate thereof, to a subject experiencing:
• diastolic dysfunction,
• cardiac fibrosis,
• pulmonary hypertension, and
• a left ventricular ejection fraction of ≥50%,
• wherein the subject does not have cardiac amyloid deposits.