Method for Medical Diagnosis Utilizing PDA Software Robots

• US 20110124975A1
• Filed: 02/04/2011
• Published: 05/26/2011
• Est. Priority Date: 03/16/2007
• Status: Abandoned Application

• Current Assignee: Arthur Solomon Thompson
• Original Assignee: Arthur Solomon Thompson
• Inventors: Thompson, Arthur Solomon
• Application Number:
  US13/020,969
• Publication Number:
  US 20110124975A1
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method for diagnosing problems using piece removal techniques and which can include establishing a health status variable, collecting and storing information from a user in the health status variable tracking the health status variable, comparing the health status variable to a knowledge base, using the health status variable to reduce the size of the knowledge base, leveraging patterns and past history to formulate a search strategy, using the search strategy to collect further diagnostic information from the user, updating the health status variable, comparing the updated health status variable to the reduced knowledge base, diagnosing a problem based on the further diagnostic information, and selecting treatment for the problem.

Claims

1. A method for diagnosing problems using piece removal techniques, comprising:

establishing a health status variable, the health status variable containing a plurality of elements corresponding to body components;

collecting information from a user regarding the status of the user'"'"'s body components;

storing the information from the user by altering the state of the corresponding elements in the health status variable;

tracking the state of the plurality of elements in the health status variable to determine patterns and past history;

comparing the health status variable to a knowledge base containing other health status variables;

reducing the size of the knowledge base by removing health status variables and objects based on the collected information, patterns, and past history;

leveraging patterns and past history associated with the health status variables remaining in the knowledge base to formulate a present search strategy;

collecting further diagnostic information from the user consistent with the present search strategy;

updating the health status variable associated with the user by altering the state of the corresponding elements in the health status variable;

comparing the updated health status variable to the reduced knowledge base;

diagnosing a problem based on the further diagnostic information; and

selecting treatment for the problem based on the further diagnostic information, patterns, and past history

2. The method of claim 1, wherein the health status variable is a binary string.

3. The method of claim 2, wherein the binary string contains approximately 200 bits.

4. The method of claim 2, wherein each bit of the binary string corresponds to a body component of the user.

5. The method of claim 4, wherein collecting information from the user further comprises changing the bit in the health status variable corresponding to each body component in a way that reflects the state of that body component.

6. The method of claim 1, further comprising storing the health status variables associated with each diagnosis in order to optimize subsequent diagnoses of the same type.

7. A method for diagnosing problems using equilibrium-reestablishing techniques, comprising:

establishing a health status variable, the health status variable containing a plurality of elements corresponding to body components;

collecting information from a user regarding the status of the user'"'"'s body components;

storing the information from the user by altering the state of the corresponding elements in the health status variable;

tracking the state of the plurality of elements in the health status variable to determine patterns and past history;

identifying differences between previous versions of the user'"'"'s health status variable and the user'"'"'s current health status variable;

collecting further diagnostic information from the user regarding those differences;

updating the health status variable associated with the user by altering the state of the corresponding elements in the health status variable;

comparing the updated health status variable to previous versions of the user'"'"'s health status variable;

diagnosing a problem based on the further diagnostic information; and

selecting treatment for the problem based on the further diagnostic information, patterns, and past history.

8. The method of claim 7, wherein the health status variable is a binary string.

9. The method of claim 8, wherein the binary string contains approximately 200 bits.

10. The method of claim 8, wherein each bit of the binary string corresponds to a body component of the user.

11. The method of claim 10, wherein collecting information from the user further comprises changing the bit in the health status variable corresponding to each body component in a way that reflects the state of that body component.

12. The method of claim 7, further comprising storing the health status variables associated with each diagnosis in order to optimize subsequent diagnoses of the same type.

13. A system for diagnosing problems using comprising:

an apparatus having a processor and a display and data entry device;

an interface for prompting and entering information;

a knowledge base housing information; and

a computer program process that establishes a health status variable, collects and stores information from a user in the health status variable, tracks the health status variable, compares the health status variable to a knowledge base, uses the health status variable to reduce the amount of the knowledge base that needs to be searched, leverages patterns and past history to formulate a search strategy, uses the search strategy to collect further diagnostic information from the user, updates the health status variable, compares the updated health status variable to the reduced knowledge base, diagnoses a problem based on the further diagnostic information, and selects treatment for the problem.