CHARACTERIZATION OF CELL WALL GLYCOPROTEINS OF PNEUMOCYSTIS CARINII: AIDS

库特勒博士和伍兹博士汇编了一组关于镰刀的数据 细胞性贫血患者。我们使用了人工神经网络 技术来确定，原则上，是否可以从 患者的初始状态，如果他/她对 羟基脲治疗，如果是，用什么剂量的药物。另一个 该项目的目标是预测 通过使用神经网络预测器监控患者数据来控制疾病。 在过去的一年里，我们已经能够训练一种人工神经 能够以85%的准确率预测患者是否 对治疗的反应是积极的。我们觉得这个 数字可以通过进一步的调查来改进。一篇论文发表了 提交给《美国医学杂志》的准备工作 协会。

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.