초록 ▼

A method useful for facilitating choosing a treatment or treatment regime and for predicting the outcome of a treatment for a disorder which is diagnosed and monitored by a physician or other appropriately trained and licensed professional, such as for example, a psychologist, based upon the symptom

A method useful for facilitating choosing a treatment or treatment regime and for predicting the outcome of a treatment for a disorder which is diagnosed and monitored by a physician or other appropriately trained and licensed professional, such as for example, a psychologist, based upon the symptoms experienced by a patient. Unipolar depression is an example of such a disorder, however the model may find use with other disorders and conditions wherein the patient response to treatment is variable. In the preferred embodiment, the method for predicting patient response includes the steps of performing at least one measurement of a symptom on a patient and measuring that symptom so as to derive a baseline patient profile, such as for example, determining the symptom profile with time; defining a set of a plurality of predictor variables which define the data of the baseline patient profile, wherein the set of predictor variables includes predictive symptoms and a set of treatment options; deriving a model that represents the relationship between patient response and the set of predictor variables; and utilizing the model to predict the response of said patient to a treatment. A neural net architecture is utilized to define a non-linear, second order model which is utilized to analyze the patient data and generate the predictive database from entered patient data.

대표청구항 ▼

[ What is claimed is:] [1.]1. An automated method for generating an expected recovery pattern for a patient having an affective disorder which is diagnosed and monitored, based upon patient symptoms, wherein patient response to treatment is variable, and wherein said patient exhibits at least one ob

[ What is claimed is:] [1.]1. An automated method for generating an expected recovery pattern for a patient having an affective disorder which is diagnosed and monitored, based upon patient symptoms, wherein patient response to treatment is variable, and wherein said patient exhibits at least one observed symptom, comprising:a.) deriving a model of expected recovery patterns from individual patterns of known symptoms and known responses to at least one treatment option;b.) providing a data system to integrate data comprising known symptoms, treatments and responses thereto, said data provided to said model, so that said model can generate a generalized expected pattern of outcome for a selected treatment when a particular pattern of symptoms is exhibited; andc.) applying said observed symptom and a proposed treatment option to said model wherein said model generates an expected recover pattern for said patient.