观点评论|菁英小记者·留学论文展示-Ruoran Zhang( 二 )
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While most of the trends align with other research in the medical field, some of the functions are confounded by flaws in the data set, but can potentially provide insight into other aspects of the parameters.
5.2 Accuracy
Mapping results >0.5 as having a heart disease and results <0.5 as not having a heart disease, the model is able to reach a 89.6% accuracy in the training set with 300 inputs and 81.1% accuracy on the testing set which has 53 inputs.
6.Conclusion
An Additive Neural Network model not only performs better than some non- additive models in analyzing the patients’ information but also gives insights into the relationship be-tween each parameter and the diagnosis of heart disease. This additive model can be applied to other diagnoses that are based on multiple test results and contributing factors and can po-tentially improve the efficiency and accuracy of such diagnosis.
References
[1]Chen, H.-L., Huang, C.-C., Yu, X.-G., Xu, X., Sun, X., Wang, G.,and Wang, S.-J. An ef-ficient diagnosis system for detection of parkin-son’s disease using fuzzy k-nearest neighbor approach.
[2]Detrano, R., Janosi, A., Steinbrunn, W., Pfisterer, M., Schmid, J.-J., Sandhu, S., Guppy, K. H., Lee, S., and Froelicher, V. In-
[3]He, K., Zhang, X., Ren, S., and Sun, J. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.
[4]Kingma, D. P., and Ba, J. Adam: A method for stochastic optimization.
[5]Lou, Y., Caruana, R., and Gehrke, J. Intelligible models for classifica- tion and regres-sion.
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姓名：Ruoran (Zora) Zhang
年龄：17岁
城市：Palo Alto
就读学校：Henry M Gunn High School
年级：12年级
目标专业：数据科学
人工智能在许多领域都有着无限的潜能 。 抱着对于机器学习在医学方面应用的好奇 ， 我开始了解不同的机器学习算法 。 本篇文章探索了神经网络的进阶——可加性神经网络 (Ad-ditive Neural Network Model) ， 以及其在一套心脏病数据中的表现 。 从阅读相关论文 ， 到运行python代码进一步改进模型 ， 再到撰写论文报告 ， 我不仅为model的成功运行感到高兴 ， 还加深了许多统计学及机器学习的知识 。
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