Hyper-fractionation of transmission history for medical diagnostic software

• US 20040143455A1
• Filed: 01/22/2003
• Published: 07/22/2004
• Est. Priority Date: 01/22/2003
• Status: Active Grant

• Current Assignee: SimulConsult, Inc.
• Original Assignee: SimulConsult, Inc.
• Inventors: Segal, Michael M.
• Granted Patent: US 7,742,932 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Abstract

The difficulties in incorporating transmission history into medical diagnostic software are non-obvious. These are addressed here with systems and methods for hyper-fractionation of transmission history in a way that allows the full power of this information to be used in medical diagnostic software.

Claims

1. A method of discriminating among a plurality of candidate diseases, comprising

identifying a set of parameters representative of component transmission mechanisms through which a disease may be transmitted,

collecting a transmission history consisting of information about presence or absence of disease in family members or others nearby,

specifying component transmission mechanisms associated with respective ones of the one or more candidate diseases,

fractionating the transmission history to identify the presence or absence of a component transmission mechanism, and

computing a probability of expecting a transmission history given presence or absence of the respective component transmission mechanisms.

2. A method according to claim 1, further comprising

employing the computed probability of expecting a transmission history given presence or absence of the respective component transmission mechanisms to modify a probability associated with a particular candidate disease.

3. A method according to claim 1, further comprising

employing the computed probability of expecting a transmission history given presence or absence of the respective component transmission mechanisms to modify probability values associated with each of the one or more candidate diseases.

4. A method according to claim 1, further comprising

displaying said probability of each said disease in rank order to a user of said computerized medical diagnosis for discrimination among said diseases.

5. The method of claim 1, wherein said classifying comprises identifying at least two forms of each transmission history, negative history and positive history.

6. The method of claim 1, wherein:

said database comprises factors accounting for mutation, penetrance, and/or error probabilities for each said disease; and

said computing further comprises modifying said probability of inheritance according to said factors.

7. The method of claim 1, wherein said transmission history comprises

information about parental consanguinity or miscarriages.

8. The method of claim 1, wherein said transmission history comprises

information about maternal uncles, more distant relatives, non-related contacts and persons sharing exposure to the same environment.

9. A computer readable medium having stored thereon instructions for directing a data processing system to implement a method of discriminating among a plurality of candidate diseases, the instructions comprising the steps of

identifying a set of parameters representative of component transmission mechanisms through which a disease may be transmitted,

collecting a transmission history consisting of information about presence or absence of disease in family members or others nearby,

specifying component transmission mechanisms associated with respective ones of the one or more candidate diseases,

fractionating the transmission history to identify the presence or absence of a component transmission mechanism, and

computing a probability of expecting a transmission history given presence or absence of the respective component transmission mechanisms.

10. A data processing apparatus for discriminating among a plurality of candidate diseases, comprising

means for identifying a set of parameters representative of component transmission mechanisms through which a disease may be transmitted,

means for collecting a transmission history consisting of information about presence or absence of disease in family members or others nearby,

means for specifying component transmission mechanisms associated with respective ones of the one or more candidate diseases,

means for fractionating the transmission history to identify the presence or absence of a component transmission mechanism, and

means for computing a probability of expecting a transmission history given presence or absence of the respective component transmission mechanisms.