使用深度学习和梯度增强树分析糖尿病患者

Rahul Deo Sah, Sibo Prasad Patro, Neelamadhab Padhy, Nagesh Salimath
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引用次数: 1

摘要

数据挖掘在疾病症状预测中发挥着重要作用。许多疾病,如心脏病预测,乳腺癌预测,糖尿病患者分析使用数据管理技术。随着信息技术的普及及其在医疗卫生领域的持续介入,糖尿病及其症状已广为人知。它有助于找到诊断和治疗疾病的解决方案。使用数据模型对数据集进行分类,用于疾病预测。分类技术是有更快和更多样化的解决方案。两种算法趋势是深度学习和另一种梯度增强树,以实现预测值32.20和27.73。深度学习的性能优于研究中出现的梯度提升树。
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Diabetics Patients Analysis Using Deep Learning and Gradient Boosted Trees
Data mining plays an important role in disease symptoms prediction. A number of diseases like prediction of heart disease, breast cancer prediction,diabetics patients analysis using data maning techniques are involved. Diabetes and their symptoms are well verse-known, as the spreading of information technology and their continued involvement in the medical and health fields. Its help to find solutions for diagnosis the dieases and treatment. Using data models to classify the dataset for predition of disease. The classification technique is to have quicker and more diverse solutions. Two algorithmic trends are Deep learning and another one Gradient Boosted Trees to achieve the predicted value 32.20 and 27.73. The Deep Learning performance is better then Gradient Boosted Trees which is appearance in the research.
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