Has the Future Started? The Current Growth of Artificial Intelligence, Machine Learning, and Deep Learning

人工智能 大数据 深度学习 计算机科学 机器学习 面子(社会学概念) 医疗保健 数据科学 社会科学 政治学 社会学 数据挖掘 法学
出处
期刊:Iraqi journal for computer science and mathematics [College of Education - Aliraqia University]
卷期号:: 115-123 被引量:185
标识
DOI:10.52866/ijcsm.2022.01.01.013
摘要

In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military. In these fields, the accurate prediction and analysis of data are crucial, regardless of how large the data are. However, using big data is confusing due to the rapid growth and massive development in public life, which requires a tremendous human effort in order to deal with such type of data and extract worthy information from it. Thus, the role of artificial intelligence begins in analyzing big data based on scientific techniques, especially in machine learning, whereby it can identify patterns of decision-making and reduce human intervention. In this regard, the significance role of artificial intelligence, machine learning and deep learning is growing rapidly. In this article, the authors decide to highlight these sciences by discussing how to develop and apply them in many decision-making domains. In addition, the influence of artificial intelligence in healthcare and the gains this science provides in the face of the COVID-19 pandemic are highlighted. This article concludes that these sciences have a significant impact, especially in healthcare, as well as the ability to grow and improve their methodology in decision-making. Additionally, artificial intelligence is a vital science, especially in the face of COVID-19.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
lizi完成签到 ,获得积分10
刚刚
刚刚
lsk发布了新的文献求助10
1秒前
打打应助ocean采纳,获得10
2秒前
panpanpan完成签到,获得积分10
3秒前
英俊的铭应助am采纳,获得10
4秒前
星辰大海应助美好芳采纳,获得10
4秒前
星辰大海应助粗心的乐松采纳,获得10
5秒前
英俊的铭应助朴素烨霖采纳,获得10
7秒前
我是老大应助lavender采纳,获得10
8秒前
panpanpan发布了新的文献求助10
8秒前
12秒前
桃桃发布了新的文献求助10
13秒前
14秒前
14秒前
自然白安发布了新的文献求助10
18秒前
zlp发布了新的文献求助10
18秒前
完美世界应助OncE采纳,获得10
19秒前
美好芳发布了新的文献求助10
19秒前
羽婕发布了新的文献求助20
19秒前
田様应助诚心的月光采纳,获得10
21秒前
轻松的纸鹤完成签到,获得积分10
23秒前
斯文蘑菇应助科研通管家采纳,获得10
24秒前
lyl19880908应助科研通管家采纳,获得10
24秒前
小蘑菇应助科研通管家采纳,获得10
24秒前
Hello应助科研通管家采纳,获得10
24秒前
WM应助科研通管家采纳,获得10
24秒前
shinysparrow应助科研通管家采纳,获得100
24秒前
情怀应助科研通管家采纳,获得10
24秒前
情怀应助科研通管家采纳,获得10
25秒前
上官若男应助科研通管家采纳,获得10
25秒前
25秒前
25秒前
SciGPT应助科研通管家采纳,获得10
25秒前
英姑应助科研通管家采纳,获得10
25秒前
搜集达人应助科研通管家采纳,获得10
25秒前
思源应助科研通管家采纳,获得10
25秒前
25秒前
隐形曼青应助科研通管家采纳,获得10
26秒前
思源应助科研通管家采纳,获得10
26秒前
高分求助中
Solution Manual for Strategic Compensation A Human Resource Management Approach 1200
Natural History of Mantodea 螳螂的自然史 1000
Glucuronolactone Market Outlook Report: Industry Size, Competition, Trends and Growth Opportunities by Region, YoY Forecasts from 2024 to 2031 800
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Zeitschrift für Orient-Archäologie 500
Smith-Purcell Radiation 500
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3343057
求助须知:如何正确求助?哪些是违规求助? 2970087
关于积分的说明 8642705
捐赠科研通 2650072
什么是DOI,文献DOI怎么找? 1451108
科研通“疑难数据库(出版商)”最低求助积分说明 672099
邀请新用户注册赠送积分活动 661407