机器学习技术及其在医疗保健中的应用综述

D. Rathore, Praveen Kumar Mannepalli
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引用次数: 4

摘要

人工智能和机器学习的一些最伟大的成功是在计算机视觉领域。计算机视觉主要研究医学成像和物体或模式识别。机器学习是人工智能技术的一个子集,指的是从过去的数据或经验中学习,然后提高特定数据集的准确性或预测比率的能力,深度学习在医疗保健部门和电子健康记录中非常流行。本文综述了机器学习和深度学习技术在医疗保健领域的一些主要特点,介绍了机器学习技术将为各种医疗保健领域提供的应用,然后回顾了作者之前在医疗保健领域的工作,并重点介绍了一些重要疾病的特征提取技术和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Machine Learning Techniques and Applications for Health Care
Some of the greatest successes of artificial intelligence and machine learning have been in the field of computer vision. Computer vision focuses on the medical imaging and objects or pattern recognition. Machine learning is a subset of artificial intelligence techniques that refers to the ability to learning form the past data or experience then improve the accuracy or prediction ratio for the particular datasets, deep leaning is very popular in the health care sectors and for the electronic health record. In this paper we review the machine learning and deep learning techniques for the health care sectors, with some key features, In this review we mentioned the machine learning techniques will be provided for the variety of applications, then review about the previous author work in health care sectors and highlight some important diseases with their feature extraction techniques and accuracy.
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