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Prediction of clinical response to treatment of Chron's disease by using RBFN
Grabec, Igor ...
This paper concerns the prediction of patient response to treatment of Crohn'sdisease with the drug infliximab. As an optimal predictor, a normalizedradial basis function neural network is utilized. ...Information used in the prediction is based on joint data from clinical parameters and responseindicators observed in a test group of patients. In the presented example, the network utilizes given oral parameters from selected patients to predict the response to drug administration. In the prediction algorithm, the similarity between the given parameters and those in the database is calculated. If is then used as a weight by which the response of a patient from the test group is predicted. The method thus resembles the prediction performed by a physician based upon comparison of a treated patient with previously tested ones. Prediction quality is estimated from the discrepancy between predicted and observed response data. Prediction quality correspondingto particular clinical parameters provides for their ordering andselection of an optimal set of parameters that together yield the maximal quality O.63 and - 80% coincidence between predicted and observed response categories.
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