A survey on artificial intelligence techniques for chronic diseases: open issues and challenges

被引：0
作者：
Keyur Patel
Chinmay Mistry
Dev Mehta
Urvish Thakker
Sudeep Tanwar
Rajesh Gupta
Neeraj Kumar
机构：
[1] Nirma University,Department of Computer Science and Engineering
[2] Deemed to be University,Thapar Institute of Engineering and Technology
[3] Asia University,Department of Computer Science and Information Engineering
[4] School of Computer Science,undefined
[5] University of Petroleum and Energy Studies,undefined
来源：
Artificial Intelligence Review | 2022年 / 55卷
关键词：
Artificial intelligence; Deep learning; Support vector machine; Convolutional neural network; Artificial neural network; Deep belief network; Chronic diseases; Cancer; Brian-related diseases; Heart-related diseases;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Artificial Intelligence (AI) has given significant solutions to the healthcare domain for analyzing various chronic diseases. With the advent of high-end systems, i.e., Graphics Processing Units, AI widespread the healthcare domain, where human experts dominate. AI techniques make the early identification and diagnosis of diseases, which aid the clinicians in mitigating the associated risk. This survey comprehensively reviews the existing literature on AI-assisted chronic disease prediction by considering cancer, heart, and brain-related diseases. However, research is underway to design and develop efficient AI techniques to aid the early prediction of diseases and render valuable insights into the patient’s profile. We conclude with the open issues and challenges faced by the current AI techniques for the prediction and early detection of chronic diseases and discuss future work in the diagnosis of these diseases.
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页码：3747 / 3800
页数：53
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