Multi-phase anchor-based diagnostic decision-support method and system

A computerized medical diagnosis method for assisting a health professional to diagnose a medical condition assuming findings are conditionally independent given any disease hypothesis comprising the steps of:

• (i) providing an anchor condition;
• (ii) associating with said anchor condition a plurality of diagnoses whose main clinical manifestation is said anchor condition;
• (iii) arranging the knowledge about a disease in sets of small Bayesian Networks (BNs), wherein each BN corresponds to one phase of a disease Knowledge-Base (KB) and comprises the relevant findings and disease hypotheses for that phase, the prior probabilities of the disease hypotheses and the conditional probabilities P(F|D) representing frequency data;
• (iv) moving from the BN of one phase to the BN of the next phase by setting the diagnosis with the highest posterior probability from the prior phase as the anchor of the BN corresponding to the next phase, wherein the prior probabilities of the diagnoses belonging to the next phase given the anchor are computed by constructing an intermediate BN comprising of the diseases or abstractions used in the DD-set of a phase and the phase's anchor condition such that the probabilities used in said intermediate BN are the prior probabilities of the diseases, and the conditional probabilities relating the anchor condition to the individual disease hypotheses P(anchor|D) are derived from the disease manifested as anchor relationships, and the computed prior probabilities of said intermediate BN serve as the prior probabilities for the diseases in the BN of the next phase;
• (v) repeating step (iv) until the diagnosis with the highest posterior probability does not serve as an anchor of a next BN and is thus determined to be the diagnosis for said medical condition.

A computerized medical diagnosis system for assisting a health professional to diagnose a medical condition, comprising:

• (i) means for providing an anchor condition;
• (ii) means for associating with said anchor condition a plurality of diagnoses whose main clinical manifestation is said anchor condition;
• (iii) means for associating with each diagnosis of said plurality of diagnoses a weight that represents the likelihood that the diagnosis is manifested as the anchor condition;
• (iv) means for associating a plurality Clinical Data Items (CDIs) with each diagnosis of said plurality of diagnoses for a given anchor condition, each combination of CDI and a diagnosis is assigned an evoking strength in which the CDI evokes the diagnosis and a penalty that the diagnosis receives in the absence of a finding;
• (v) means for calculating a total weighted score for each possible diagnosis of the patient among the plurality of diagnoses by adding for each diagnosis:
• the likelihood that the diagnosis is manifested as the anchor, the evoking strengths of each CDI that is true for the patient and subtracting for each CDI that is absent in the patient the penalty weight for defined penalty relationships between the diagnosis and the CDIs;
• (vi) means for choosing a diagnosis above a cutoff level of the weighted score and making it an anchor condition;
• and
• (vii) means for repeating steps (ii) through (vi) until the diagnosis with the highest weighted score, which now serves as an anchor condition, does not have any associated diagnoses and is thus determined to be the diagnosis for said medical condition.

A computer-readable medium encoded with a program module that executes a medical diagnosis method for assisting a health professional to diagnose a medical condition, by:

• (i) providing an anchor condition;
• (ii) associating with said anchor condition a plurality of diagnoses whose main clinical manifestation is said anchor condition;
• (iii) associating with each diagnosis of said plurality of diagnoses a weight that represents the likelihood that the diagnosis is manifested as the anchor condition;
• (iv) associating a plurality Clinical Data Items (CDIs) with each diagnosis of said plurality of diagnoses given an anchor condition, each combination of CDI and a diagnosis is assigned an evoking strength in which the CDI evokes the diagnosis and a penalty that the diagnosis receives in the absence of a finding;
• (v) calculating a total weighted score for each possible diagnosis of the patient among the plurality of diagnoses by adding for each diagnosis:
• the likelihood that the diagnosis is manifested as the anchor, the evoking strengths of each CDI that is true for the patient and subtracting for each CDI that is absent in the patient the penalty weight for defined penalty relationships between the diagnosis and the CDIs;
• (vi) choosing the diagnosis above a cutoff level of the weighted score and making it an anchor condition;
• and
• (vii) repeating steps (ii) through (vi) until the diagnosis with the highest weighted score, which now serves as an anchor condition, does not have any associated diagnoses and is thus determined to be the diagnosis for said medical condition.