Expert system for determining patient treatment response

A computer-implemented method for predicting patient response to treatment for a subject patient, the method comprising:

• receiving, for a subject patient, a subject patient dataset including features obtained for a reduced feature dataset;
• and
• comparing the subject patient dataset to a feature data scheme to predict a response for the subject patient;
• wherein the feature data scheme comprises:
• (a) a diagnostic model for determining a diagnosis of one of a plurality of known disorders indicated by an individual patient dataset;
• and
• (b) a plurality of diagnosis-specific treatment response models, each of the diagnosis-specific treatment response models corresponding to a specific diagnosis of one of the known disorders, the treatment response models configured to use feature data to predict treatment response;
• wherein comparing the subject patient dataset to the feature data scheme to predict the response for the subject patient comprises:
• applying the diagnostic model to the subject patient dataset to determine a subject patient diagnosis of one of the known disorders indicated for the subject patient by the subject patient dataset;
• and
• selecting and applying one of the diagnosis-specific treatment response models to the subject patient dataset to predict the response for the subject patient;
• wherein the selected diagnosis-specific treatment response model corresponds to the determined subject patient diagnosis.

A medical system comprising:

• a first computer, wherein the first computer comprises:
• storage for storing a feature data scheme, wherein the feature data scheme comprises:
• (a) a diagnostic model for determining a diagnosis of one of a plurality of known disorders indicated by an individual patient dataset;
• and
• (b) a plurality of diagnosis-specific treatment response models, each of the diagnosis-specific treatment response models corresponding to a specific diagnosis of one of the known disorders, the treatment response models configured to use feature data to predict treatment response;
• and
• at least one processor coupled to the storage and to an input device, the processor executing instructions for:
• receiving, for a subject patient, a subject patient dataset including features obtained for a reduced feature dataset;
• and
• comparing the subject patient dataset to a feature data scheme to predict a response for the subject patient;
• wherein comparing the subject patient dataset to the feature data scheme to predict the response for the subject patient comprises:
• applying the diagnostic model to the subject patient dataset to determine a subject patient diagnosis of one of the known disorders indicated for the subject patient by the subject patient dataset;
• and
• selecting and applying one of the diagnosis-specific treatment response models to the subject patient dataset to predict the response for the subject patient;
• and wherein the selected diagnosis-specific treatment response model corresponds to the determined subject patient diagnosis.

A computer-implemented method for assessment of status of a patient, the method comprising:

• receiving, for a subject patient, a subject patient dataset including features obtained for a reduced feature dataset;
• and
• comparing the subject patient dataset to a feature data scheme to allocate an assessment status for the subject patient;
• wherein the feature data scheme comprises:
• (a) a diagnostic model for determining a diagnosis of one of a plurality of known disorders indicated by an individual patient dataset;
• and
• (b) a plurality of diagnosis-specific assessment status models, each of the diagnosis-specific assessment status models corresponding to a specific diagnosis of one of the known disorders, the assessment status models configured to use feature data to allocate an assessment status;
• wherein comparing the subject patient dataset to the feature data scheme to allocate the assessment status for the subject patient comprises:
• applying the diagnostic model to the subject patient dataset to determine a subject patient diagnosis of one of the known disorders indicated for the subject patient by the subject patient dataset;
• and
• selecting and applying one of the diagnosis-specific assessment status models to the subject patient dataset to allocate the assessment status for the subject patient;
• and wherein the selected diagnosis-specific assessment status model corresponds to the determined subject patient diagnosis.

A medical system comprising:

• a computer, wherein the computer comprises:
• storage for storing a feature data scheme, wherein the feature data scheme comprises:
• (a) a diagnostic model for determining a diagnosis of one of a plurality of known disorders indicated by an individual patient dataset;
• and
• (b) a plurality of diagnosis-specific assessment status models, each of the diagnosis-specific assessment status models corresponding to a specific diagnosis of one of the known disorders, the assessment status models configured to use feature data to allocate an assessment status;
• at least one processor coupled to the storage and to an input device, the processor executing instructions for:
• receiving, for a subject patient, a subject patient dataset including features obtained for a reduced feature dataset;
• and
• comparing the subject patient dataset to a feature data scheme to allocate an assessment status for the subject patient;
• wherein comparing the subject patient dataset to the feature data scheme to allocate the assessment status for the subject patient comprises:
• applying the diagnostic model to the subject patient dataset to determine a subject patient diagnosis of one of the known disorders indicated for the subject patient by the subject patient dataset;
• and
• selecting and applying one of the diagnosis-specific assessment status models to the subject patient dataset to allocate the assessment status for the subject patient;
• and wherein the selected diagnosis-specific assessment status model corresponds to the determined subject patient diagnosis.