找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Artificial Intelligence and Machine Learning for Healthcare; Vol. 2: Emerging Met Chee Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain Book 2023 Th

[復(fù)制鏈接]
查看: 24704|回復(fù): 44
樓主
發(fā)表于 2025-3-21 16:58:44 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Artificial Intelligence and Machine Learning for Healthcare
期刊簡(jiǎn)稱Vol. 2: Emerging Met
影響因子2023Chee Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain
視頻videohttp://file.papertrans.cn/163/162239/162239.mp4
發(fā)行地址Presents a sample of recent advances in the theory and applications of artificial intelligence paradigms.Written in a coherent and well-founded way.Case studies demonstrate the real world applications
學(xué)科分類Intelligent Systems Reference Library
圖書(shū)封面Titlebook: Artificial Intelligence and Machine Learning for Healthcare; Vol. 2: Emerging Met Chee Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain Book 2023 Th
影響因子.In line with advances in digital and computing systems, artificial intelligence (AI) and machine learning (ML) technologies have transformed many aspects of medical and healthcare services, delivering tangible benefits to patents and the general public. This book is a sequel of the edition on “Artificial Intelligence and Machine Learning for Healthcare”. The first volume is focused on utilization of AI and ML for image and data analytics in the medical and healthcare domains. In this second volume, emerging methodologies and future trends in AI and ML for advancing medical treatments and healthcare services are presented. The selected studies in this book provide readers a glimpse on current progresses in AI and ML for undertaking a variety of healthcare-related tasks. The advances in AI and ML technologies for future healthcare are also discussed, shedding light on the potential of AI and ML to realize the next-generation medical treatments and healthcare services for the betterment of our global society. .
Pindex Book 2023
The information of publication is updating

書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare影響因子(影響力)




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare影響因子(影響力)學(xué)科排名




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare被引頻次




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare被引頻次學(xué)科排名




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare年度引用




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare年度引用學(xué)科排名




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare讀者反饋




書(shū)目名稱Artificial Intelligence and Machine Learning for Healthcare讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-22 00:17:57 | 只看該作者
板凳
發(fā)表于 2025-3-22 04:18:47 | 只看該作者
地板
發(fā)表于 2025-3-22 07:50:55 | 只看該作者
5#
發(fā)表于 2025-3-22 11:12:03 | 只看該作者
6#
發(fā)表于 2025-3-22 14:26:49 | 只看該作者
https://doi.org/10.1007/3-540-28051-0re and to consequently identify its role. Based on a Systematic Literature Review (SLR), the following application areas for key determinants in healthcare have been identified: ., ., . and .. By means of structural equation modeling (SEM), the study confirmed . and . as positive and significant inf
7#
發(fā)表于 2025-3-22 17:36:54 | 只看該作者
8#
發(fā)表于 2025-3-22 21:34:22 | 只看該作者
Artificial Intelligence for the Future of Medicine, in electronic medical records, pharmacological data, etc. These data have grown exponentially and efforts to improve their quality are already paying off. However, it is no longer possible for a health professional to analyze them to provide a better diagnosis or carry out preventive work on diseas
9#
發(fā)表于 2025-3-23 02:52:57 | 只看該作者
Social Media Sentiment Analysis Related to COVID-19 Vaccinations,ataset retrieved from Kaggle, which contains COVID-19 vaccine-related Twitter data. When attempting to perform sentiment analysis, certain methodological steps need to be considered after data collection, including data pre-processing, technique selection and model construction, as well as model eva
10#
發(fā)表于 2025-3-23 08:58:49 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-23 22:33
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
江都市| 和政县| 米脂县| 云龙县| 南投县| 凤台县| 济宁市| 太谷县| 吉安县| 兰溪市| 湘潭县| 禹城市| 宜阳县| 柘城县| 运城市| 大方县| 盐边县| 松溪县| 芒康县| 富顺县| 同江市| 阿拉尔市| 六安市| 化隆| 肥城市| 黔西县| 阳城县| 塔河县| 宜都市| 禄丰县| 桓仁| 临江市| 卫辉市| 双流县| 昆明市| 玉门市| 库伦旗| 黎城县| 兴隆县| 徐汇区| 舟山市|