METHOD AND SYSTEM FOR SUPPORTING A CLINICAL DIAGNOSIS

• US 20130310653A1
• Filed: 05/16/2012
• Published: 11/21/2013
• Est. Priority Date: 05/16/2012
• Status: Active Grant

• Current Assignee: Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens AG
• Inventors: Zillner, Sonja, Oberkampf, Heiner
• Granted Patent: US 8,965,818 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Methods and systems may support conclusions of a clinician by enabling the clinician to arbitrarily define the symptoms according to the patient'"'"'s record. The method may comprise: (a) determining a plurality of symptoms representing a patient and including characteristics of the patient, the symptoms being categorized as present symptoms, absent symptoms or open symptoms; (b) establishing a multi-tier relationship between said symptoms and a plurality of diseases based on a knowledge model; (c) adjusting weighting factor(s) for at least one multi-tier relationship based on said knowledge model; (d) optionally adjusting at least one weighting factor of step (c) by an expert; and (e) building a ranking of diseases from said multi-tier relationship based on said weighting factors. The method may provide an efficient ranking of disease information, thereby supporting a clinical diagnosis that may consider multiple symptoms while emphasizing particular symptoms in view of the clinician'"'"'s expertise.

Claims

1. An automated method for supporting a clinical diagnosis, comprising:

storing a plurality of symptoms associated with a patient, the symptoms including characteristics of the patient, wherein each symptom is categorized as a present symptom, an absent symptom, or an open symptom;

a processor establishing a multi-tier relationship between said plurality of symptoms and a plurality of diseases;

the processor adjusting at least one weighting factor for at least one (a) at least one of said multi-tier relationships and (b) at least one of said symptoms, based on a knowledge model; and

the processor building a ranking of diseases from said multi-tier relationship based on said weighting factors.

2. The method of claim 1, wherein said multi-tier relationship between said plurality of symptoms and said plurality of diseases is implemented by a bipartite graph, the bipartite graph including a plurality of nodes with each node assigned to a symptom or disease, the bipartite graph including a plurality of edges expressing a particular relationship between a particular symptom and a particular disease.

3. The method of claim 1, wherein said weighting factors include at least one of a consideration of a patient-specific incidence of a disease, a strength of a disease-symptom relation, and an importance of a symptom.

4. A system for supporting a clinical diagnosis, the system comprising:

a semantic patient record module storing semantically annotated symptoms associated with a patient, the symptoms including characteristics of the patient, wherein each symptom is categorized as a present symptom, an absent symptom, or an open symptom;

a weighted disease-symptom module including a knowledge model configured to establish a multi-tier relationship between said plurality of symptoms and a plurality of diseases;

the weighted disease-symptom module configured for adjusting at least one weighting factor for at least one (a) at least one of said multi-tier relationships and (b) at least one of said symptoms, based on a medical ontology module;

the weighted disease-symptom module configured for building a ranking of diseases from said multi-tier relationship weighted by said weighting factors;

wherein the weighted disease-symptom module is embodied by software stored in a non-transitory computer-readable medium and executable by a processor.