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

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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
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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
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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
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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
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