Diagnostic Tool

Abstract

Disclosed herein is a method for diagnosing a medical condition in a patient. The method comprises: obtaining, from the patient, a plurality of physiological values; implementing a first model configured to determine risk values for at least one of a plurality of medical conditions, based on the physiological values. Implementing the first model comprises: obtaining a first risk value for the at least one medical condition, based on a first one of the obtained physiological values; and weighting the first risk value based on a second one of the obtained physiological values, to determine a total risk value of the at least one medical condition for the patient.

What is claimed is: 
     
         1 . A method for diagnosing a medical condition in a patient, the method comprising:
 obtaining, from the patient, a plurality of physiological values;   implementing a first model configured to determine risk values for at least one of a plurality of medical conditions, based on the physiological values;
 wherein implementing the first model comprises: 
   obtaining a first risk value for the at least one medical condition, based on a first one of the obtained physiological values; and   weighting the first risk value based on a second one of the obtained physiological values, to determine a total risk value of the at least one medical condition for the patient.   
     
     
         2 . The method of  claim 1  wherein implementing the first model comprises sequentially weighting the risk value for the at least one medical condition, by each of the plurality of physiological values in turn. 
     
     
         3 . The method of  claim 1 , further comprising comparing each of the total risk values with a selected threshold, and, in the event that one or more of the total risk values exceeds the corresponding threshold, selecting at least one diagnosis pathway for diagnosing the corresponding medical condition. 
     
     
         4 . The method of  claim 3 , wherein selecting a diagnosis pathway comprises implementing a second model configured to select at least one of a plurality of possible diagnosis pathways, based on a plurality of sets of pathway parameter values, wherein each set is associated with one of the diagnosis pathways. 
     
     
         5 . The method of  claim 4 , wherein implementing the second model comprises, in the event that one of the pathway parameter values meets a threshold value, selecting the associated diagnosis pathway. 
     
     
         6 . The method of  claim 4 , further comprising: obtaining a diagnosis pathway data set for one of a plurality of diagnosis pathways, said pathway data set comprising a plurality of pathway parameter values for that diagnosis pathway; and modifying the second model, based on the pathway data set. 
     
     
         7 . The method of  claim 6 , wherein modifying the second model comprises weighting each of the pathway parameter values associated with that diagnosis pathway in the second model, by the corresponding obtained pathway parameter value. 
     
     
         8 . The method of  claim 1 , further comprising:
 obtaining a patient data set comprising:   a set of physiological values; and   a set of indications each identifying the presence or absence of a diagnosis of one of the plurality of medical conditions; and   modifying the first model based on the patient data set.   
     
     
         9 . A tangible non-transitory computer program product comprising program instructions configured to program configured to program a processor to perform the method of  claim 1 . 
     
     
         10 . A method for diagnosing a medical condition in a patient, the method comprising:
 obtaining, from the patient, a plurality of physiological values;   
       mapping the physiological values to a plurality of associated medical conditions;
 determining, based on the mapped physiological values, a total risk value associated with each of the medical conditions; 
 comparing each of the total risk values with a threshold; and 
 in the event that the total risk value for a condition exceeds the threshold, outputting diagnosis pathway data for diagnosing the medical condition. 
 
     
     
         11 . The method of  claim 10 , further comprising:
 obtaining risk data indicating predetermined associations between a plurality of physiological parameters and the plurality of medical conditions; wherein   mapping the physiological values to the plurality of medical conditions; and   determining the total risk value for each of the medical conditions;   is based on the risk data.   
     
     
         12 . The method of  claim 10 , wherein outputting diagnosis pathway data comprises selecting at least one out of a plurality of possible diagnosis pathways. 
     
     
         13 . The method of  claim 12 , further comprising modifying the total risk value for at least one of the conditions, based on the previous patient data. 
     
     
         14 . The method of  claim 10 , wherein determining a total risk value associated with each medical condition comprises determining, for each physiological value, an indication of the risk associated with each of the medical conditions to which it is mapped. 
     
     
         15 . The method of  claim 10 , wherein the determination of a total risk value for a condition comprises iterating over previous patient data. 
     
     
         16 . The method of  claim 15 , wherein outputting diagnosis pathway data comprises selecting at least one out of a plurality of possible diagnosis pathways; the method further comprising:
 obtaining, for each of the possible diagnosis pathways, a plurality of pathway parameter values;   wherein selecting at least one of the pathways is based on the pathway parameter values; the method further comprising modifying the pathway parameter values based on the previous patient data.   
     
     
         17 . A method of training an artificial neural network for diagnosing a medical condition, the method comprising:
 implementing, as a neural network, a first model configured to provide an association between:
 a set of physiological parameters, and 
 a risk value for at least one of a plurality of medical conditions, 
   to output an indication of the total risk for the at least one medical condition from obtained physiological values corresponding to the physiological parameters;   obtaining a patient data set comprising:   a set of physiological values; and   a set of indications each identifying the presence or absence of a diagnosis of one of the plurality of medical conditions; and   modifying the first model based on the patient data set.   
     
     
         18 . The method of  claim 17 , further comprising obtaining a plurality of said patient data sets, and iteratively modifying the first model based on each of the patient data sets. 
     
     
         19 . The method of  claim 17 , wherein the patient data set further comprises a pathway data set for one of a plurality of diagnosis pathways, said pathway data set comprising a plurality of pathway parameter values for that pathway, the method further comprising:
 implementing, as a neural network, a second model configured to:   a) provide an association between each of the plurality of pathway parameters and each of the plurality of diagnosis pathways; and   b) to select one of the diagnosis pathways based on the modified second model and the obtained physiological values; and   modifying the second model, based on the pathway data set.   
     
     
         20 . The method of  claim 19 , wherein the patient data set further comprises a pathway data set for one of a plurality of diagnosis pathways, said pathway data set comprising a plurality of pathway parameter values for that pathway, the method further comprising:
 implementing, as a neural network, a second model configured to:   a) provide an association between each of the plurality of pathway parameters and each of the plurality of diagnosis pathways; and   b) to select one of the diagnosis pathways based on the modified second model and the obtained physiological values; and   modifying the second model, based on the pathway data set;   the method further comprising iteratively modifying the second model based on each of the patient data sets.