CHARACTERIZATION OF CELL WALL GLYCOPROTEINS OF PNEUMOCYSTIS CARINII: AIDS

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Drs. Kutlar and Woods have compiled a set of data from sickle cell anemia patients. We have used artificial neural network technology to determine, in principle, whether it can be decided from the initial condition of a patient if he/she will respond to hydroxyurea treatment, and if so, at what dosage of the drug. Another goal of the project is to predict the course of development of the disease by monitoring patient data with a neural network predictor. During this past year, we have been able to train an artificial neural network that can predict with 85% accuracy whether or not a patient is going to respond positively to the treatment. We feel that this number can be improved by further investigation. A paper is in preparation for submission to the Journal of the American Medical Association.