Machine learning algorithms for smart and intelligent healthcare system in Society 5.0

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ikhlas Fuad Zamzami, Kuldeep Pathoee, Brij B. Gupta, Anupama Mishra, Deepesh Rawat, Wadee Alhalabi
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引用次数: 4

Abstract

The pandemic has shown us that it is quite important to keep track record our health digitally. And at the same time, it also showed us the great potential of Instruments like wearable observing gadgets, video conferences, and even talk bots driven by artificial intelligence (AI) can provide good care from remotely. Real time data collected from different health care devices of cases across globe played an important role in combatting the virus and also help in tracking its progress. The evolution of biomedical imaging techniques, incorporated sensors, and machine learning (ML) in recent years has led in various health benefits. Medical care and biomedical sciences have become information science fields, with a solid requirement for refined information mining techniques to remove the information from the accessible data. Biomedical information contains a few difficulties in information investigation, including high dimensionality, class irregularity, and low quantities of tests. AI is a subfield of AI and computer science which centric the utilization of information and calculations to impersonate the way that people learn, steadily further developing its accuracy. ML is an essential element of the rapidly growing area of information science. Calculations are created using measurable procedures to make characterizations or forecasts, exposing vital experiences inside information mining operations. In this chapter, we explain and compare the different algorithms of ML which could be helpful in detecting different disease at earlier stage. We summarize the algorithms and different steps involved in ML to extract information for betterment of the society which is already exposed to the world of data.

社会5.0中智能医疗保健系统的机器学习算法
这场大流行向我们表明,以数字方式记录我们的健康状况非常重要。与此同时,它也向我们展示了可穿戴观察设备、视频会议、甚至由人工智能(AI)驱动的聊天机器人等设备的巨大潜力,这些设备可以远程提供良好的护理。从全球不同医疗设备收集的病例实时数据在抗击该病毒方面发挥了重要作用,也有助于跟踪其进展。近年来,生物医学成像技术、集成传感器和机器学习(ML)的发展带来了各种健康益处。医疗保健和生物医学已成为信息科学领域,迫切需要精细化的信息挖掘技术来从可访问的数据中删除信息。生物医学信息在信息调查中存在维度高、类别不规则、测试数量少等困难。人工智能是人工智能和计算机科学的一个子领域,它以利用信息和计算来模拟人们学习的方式为中心,稳步进一步发展其准确性。ML是快速发展的信息科学领域的重要组成部分。使用可测量的程序创建计算,以进行特征描述或预测,揭示信息挖掘操作中的重要经验。在本章中,我们解释和比较了不同的机器学习算法,这些算法可以帮助在早期发现不同的疾病。我们总结了机器学习中涉及的算法和不同步骤,以提取信息,以改善已经暴露于数据世界的社会。
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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来源期刊
International Journal of Intelligent Systems
International Journal of Intelligent Systems 工程技术-计算机:人工智能
CiteScore
11.30
自引率
14.30%
发文量
304
审稿时长
9 months
期刊介绍: The International Journal of Intelligent Systems serves as a forum for individuals interested in tapping into the vast theories based on intelligent systems construction. With its peer-reviewed format, the journal explores several fascinating editorials written by today''s experts in the field. Because new developments are being introduced each day, there''s much to be learned — examination, analysis creation, information retrieval, man–computer interactions, and more. The International Journal of Intelligent Systems uses charts and illustrations to demonstrate these ground-breaking issues, and encourages readers to share their thoughts and experiences.
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