Prediction of Cardio Vascular Disease by Deep Learning and Machine Learning-A Combined Data Science Approach

A. A. Romalt, R. Kumar
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引用次数: 1

Abstract

Machine learning is the process in which the computer system can automatically learn from the data. It's an application of Artificial Intelligence without being explicitly programmed. Making use of Machine learning and AI an efficient algorithm for prediction of Cardio Vascular Disease (CVD) can be done. By combing Deep learning method to the ML model, a high-level abstract feature with improved performance can be obtained. Heart disease or Cardio Vascular disease is the predominant disease all over the world. Accurate prediction of heart disease is a challenging task. The accuracy of prediction can be improved by applying Machine learning algorithms. Results with high accuracy can be produced by combining a Machine learning model with Statistical concepts. The main objective of this research is to predict high accurate CVD by applying Deep learning model combined with Machine learning algorithm. By recognizing the symptoms of the disease, people can get prompt treatment on time.
基于深度学习和机器学习的心血管疾病预测——一种结合数据科学的方法
机器学习是计算机系统自动从数据中学习的过程。它是人工智能的一种应用,没有明确的编程。利用机器学习和人工智能可以实现有效的预测心血管疾病(CVD)的算法。通过将深度学习方法与机器学习模型相结合,可以获得性能提高的高级抽象特征。心脏病或心血管疾病是全世界的主要疾病。准确预测心脏病是一项具有挑战性的任务。应用机器学习算法可以提高预测的准确性。通过将机器学习模型与统计概念相结合,可以产生高精度的结果。本研究的主要目的是将深度学习模型与机器学习算法相结合,实现对CVD的高精度预测。通过识别疾病的症状,人们可以及时得到治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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