Computer-based neural network system and method for medical diagnosis and interpretation
First Claim
1. A method for diagnosis of a medical condition comprising the steps of:
- providing a plurality of input parameters representing characteristics of the medical condition;
converting said plurality of input parameters into numerical data;
inputting the numerical data to a neural network trained to detect the medical condition and determining a score indicative of the likelihood of the medical condition on the basis of the numerical data;
interpreting the numerical data to provide estimates of the contribution of input parameters to the determined score; and
displaying the determined score and the provided estimates in a human-readable form.
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Accused Products
Abstract
A neural network system and method for diagnosing patients'"'"' medical conditions provide an efficient aid in identifying and interpreting factors which are significant in the medical diagnosis. The neural network is trained to recognize medical conditions by being provided with input data that is available for a number of patients, and diagnosis made by physicians in each case. Upon completion of the training period the neural network system uses input measurement and interview data to produce a score, or a graded classification, of a patient'"'"'s medical condition that is accompanied with a diagnosis interpretation. The interpretation is a sorted catalogue of individual factors and interactions that influenced the score. The interpretive facility of the present invention is based on comparison with a set of nominal values for each input factor or interaction. It can assist the physician in making a diagnosis of the patient'"'"'s condition and can further provide a "second opinion" that may confirm the physician'"'"'s findings or point to ambiguities that call for a more detailed analysis.
264 Citations
29 Claims
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1. A method for diagnosis of a medical condition comprising the steps of:
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providing a plurality of input parameters representing characteristics of the medical condition; converting said plurality of input parameters into numerical data; inputting the numerical data to a neural network trained to detect the medical condition and determining a score indicative of the likelihood of the medical condition on the basis of the numerical data; interpreting the numerical data to provide estimates of the contribution of input parameters to the determined score; and displaying the determined score and the provided estimates in a human-readable form. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for diagnosis and interpretation of a medical condition comprising:
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means for providing a plurality of input parameters representing characteristics of the medical condition, the plurality of input parameters being provided as numerical data; a neural network trained to detect the medical condition for determining a score indicative of the likelihood of the medical condition on the basis of the numerical data; means for interpreting the numerical data to provide estimates of the contribution of input parameters to the determined score; and display means for displaying the determined score and the provided estimates in a human-readable form. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A computer-based system to assist the diagnosis of a medical condition, comprising:
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a patient record comprising numerical data representing a plurality of input factors associated with characteristics of the medical condition; a neural network responsive to said patient record and configured to determine a score indicative of the likelihood of the medical condition in the patient record; a computer interpreter responsive to said patient record for estimating the contribution of said plurality of input factors to the score determined in the neural network; and a display for displaying the determined score and the estimates provided by the interpreter in a human-readable form to assist the diagnosis of the medical condition. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29)
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Specification