| 摘要 |
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. |
