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標題: Titlebook: Enhanced Telemedicine and e-Health; Advanced IoT Enabled Gon?alo Marques,Akash Kumar Bhoi,Begonya Garcia-Za Book 2021 The Editor(s) (if app [打印本頁]

作者: Polk    時間: 2025-3-21 19:18
書目名稱Enhanced Telemedicine and e-Health影響因子(影響力)




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書目名稱Enhanced Telemedicine and e-Health網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Enhanced Telemedicine and e-Health被引頻次




書目名稱Enhanced Telemedicine and e-Health被引頻次學(xué)科排名




書目名稱Enhanced Telemedicine and e-Health年度引用




書目名稱Enhanced Telemedicine and e-Health年度引用學(xué)科排名




書目名稱Enhanced Telemedicine and e-Health讀者反饋




書目名稱Enhanced Telemedicine and e-Health讀者反饋學(xué)科排名





作者: 手術(shù)刀    時間: 2025-3-21 20:43
Telemedicine in the Current New Normal: Opportunities and Barriersrent in the current new normal. A blended approach comprising both classical and telemedicine practices is going to be the current new normal in healthcare. Therefore, the authors explore telemedicine at a glance and the roles of Internet of Things (IoT) and Artificial Intelligence (AI) in telemedic
作者: 凝乳    時間: 2025-3-22 02:57
Teledentistry: A New Approach in Dental Medicinehile still maintaining social distancing measures. The objective of this chapter is to update the most relevant information on the use of TD, its advantages and disadvantages as well as the most important ethical and legal aspects. It has been observed that, in general, TD can be a useful instrument
作者: GOAD    時間: 2025-3-22 07:51
Smart Management of Telemedicine Rooms in an e-Hospital Emergency Departmentlife quality. In healthcare, the use of telemedicine can provide high-quality services for medical evaluation without location restrictions. Telemedicine can significantly improve service quality, personnel management, and resource utilization in the emergency department, reducing operational budget
作者: surmount    時間: 2025-3-22 11:26

作者: 大方不好    時間: 2025-3-22 14:21
IoT for Enhanced Decision-Making in Medical Information Systems: A Systematic Reviewmedical errors and enhance patient safety, and save time for critical situations. IoT-based technologies transform medical decision-making by offering various services such as transmitting medial data/biomedical signals, patient tracking and remote monitoring, reliable access to medical data, and qu
作者: 大方不好    時間: 2025-3-22 17:27

作者: Perennial長期的    時間: 2025-3-23 00:53
Machine Learning and Internet of Things for Smart Living: A Comprehensive Review and AnalysisoT) applications to enhance quality and efficiency. This study aims to analyze the taxonomy of machine learning algorithms used in the specific type of IoT smart living applications. This chapter demonstrates an analysis of the data extracted from the 52 peer-reviewed scientific publications describ
作者: 小蟲    時間: 2025-3-23 02:19

作者: 得罪人    時間: 2025-3-23 08:17
MIoT-Based Big Data Analytics Architecture, Opportunities and Challenges for Enhanced Telemedicine Sienced its rapid acceptance in the health industry with an emphasis on designing smart applications like the tracking system for healthcare, medical assessment, forecasting, healthcare monitoring systems, and smart medical services. Medical Internet of Things (MIoT) provides a forum for gadgets and
作者: insurrection    時間: 2025-3-23 13:32

作者: defray    時間: 2025-3-23 17:45
Artificial Intelligence and Machine Learning for Health Risks Predictionare solutions. This chapter explores how applications of machine learning in the healthcare sector have sought progress, and extricate the challenges with respect to early prediction of chronic illnesses. The review of past work in this fast-growing research and development area, as well as the stat
作者: MONY    時間: 2025-3-23 18:24

作者: musicologist    時間: 2025-3-24 00:13
Disease Prediction Using Artificial Intelligence: A Case Study on Epileptic Seizure Predictionc solution for understanding require being competent as well. Biomedical data related to different diseases are recorded from a body, which can be at the organ level, cell level or molecular level. Biomedical data is mainly utilized to predict, diagnose or identify particular physiological or pathol
作者: VOC    時間: 2025-3-24 03:39
A Novel Wrapper-Based Feature Selection for Heart Failure Prediction Using an Adaptive Particle Swaro meet the needs of the body. This means that the heart is overworked and unable to respond to the speed and demands of other activities. This will lead to fatigue and shortness of breath while performing daily activities. In this research, the authors apply a machine learning model to predict heart
作者: neurologist    時間: 2025-3-24 08:35

作者: 火海    時間: 2025-3-24 12:50
1434-9922 account the emerging requirements of enhanced telemedicine In recent years, new applications on computer-aided technologies for telemedicine have emerged. Therefore, it is essential to capture this growing research area concerning the requirements of telemedicine. This book presents the latest find
作者: 沒血色    時間: 2025-3-24 17:17

作者: 令人悲傷    時間: 2025-3-24 19:10
Book 2021earch area concerning the requirements of telemedicine. This book presents the latest findings on soft computing, artificial intelligence, Internet of Things and related computer-aided technologies for enhanced telemedicine and e-health. Furthermore, this volume includes comprehensive reviews descri
作者: novelty    時間: 2025-3-25 00:24

作者: annexation    時間: 2025-3-25 04:28
978-3-030-70113-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
作者: Hemoptysis    時間: 2025-3-25 08:04
Enhanced Telemedicine and e-Health978-3-030-70111-6Series ISSN 1434-9922 Series E-ISSN 1860-0808
作者: 招致    時間: 2025-3-25 13:23

作者: 激怒    時間: 2025-3-25 18:06

作者: 過份好問    時間: 2025-3-25 22:46
https://doi.org/10.1007/978-3-030-55525-2gnostics to patients anytime, anywhere. These new developments have drawn significant attention, especially in underserved communities as well as during crises and emergencies. However, in order to successfully implement these technologies and provide adequate care, various challenges need to be tac
作者: 流動性    時間: 2025-3-26 02:53
https://doi.org/10.1007/978-3-319-57783-8rent in the current new normal. A blended approach comprising both classical and telemedicine practices is going to be the current new normal in healthcare. Therefore, the authors explore telemedicine at a glance and the roles of Internet of Things (IoT) and Artificial Intelligence (AI) in telemedic
作者: 使堅硬    時間: 2025-3-26 07:50
https://doi.org/10.1007/978-981-99-1248-3hile still maintaining social distancing measures. The objective of this chapter is to update the most relevant information on the use of TD, its advantages and disadvantages as well as the most important ethical and legal aspects. It has been observed that, in general, TD can be a useful instrument
作者: cognizant    時間: 2025-3-26 09:11
The Pedagogy of Self-Authorshiplife quality. In healthcare, the use of telemedicine can provide high-quality services for medical evaluation without location restrictions. Telemedicine can significantly improve service quality, personnel management, and resource utilization in the emergency department, reducing operational budget
作者: 駭人    時間: 2025-3-26 14:02

作者: Acetaminophen    時間: 2025-3-26 19:11

作者: 不易燃    時間: 2025-3-27 00:22

作者: 真實的你    時間: 2025-3-27 01:27

作者: Decibel    時間: 2025-3-27 08:24
https://doi.org/10.1007/978-1-4614-8758-6tems. These sensors are connected to the Internet for efficient data dissemination from anywhere and anytime so that it is called Internet of Things (IoT). Data can be processed in Cloud Computing (CC) for analysis and comparison. To reduce the latency of retrieving data from sensitive applications,
作者: 露天歷史劇    時間: 2025-3-27 11:53

作者: 傷心    時間: 2025-3-27 14:46
https://doi.org/10.1007/978-1-349-00652-6present a review of recent developments and applications of the Internet of Things (IoT) for an enhanced medical decision. The main findings in this work have been to identify how intelligent systems can help improve the medical decision-making process, making an expanded summary of the area and poi
作者: 血統(tǒng)    時間: 2025-3-27 20:36

作者: FLINT    時間: 2025-3-27 23:02
https://doi.org/10.1007/1-4020-3526-8mber of cancer cases is growing yearly, medical systems are an essential tool to speed up the diagnosis process and increase patient survival probabilities. Electronic health record systems store the patient’s health data, which can be of structured and unstructured types. Physicians use all the inf
作者: 朋黨派系    時間: 2025-3-28 04:39

作者: Virtues    時間: 2025-3-28 08:28
https://doi.org/10.1057/9780230510098o meet the needs of the body. This means that the heart is overworked and unable to respond to the speed and demands of other activities. This will lead to fatigue and shortness of breath while performing daily activities. In this research, the authors apply a machine learning model to predict heart
作者: 膽汁    時間: 2025-3-28 13:44

作者: Supplement    時間: 2025-3-28 15:15
https://doi.org/10.1007/978-3-030-70111-6Soft Computing for Telemedicine; Soft Computing for Enhanced Medical Decision and Diagnostics; Interne
作者: Prologue    時間: 2025-3-28 20:53
Research Challenges and Opportunities Towards a Holistic View of Telemedicine Systems: A Systematic igning effective Telemedicine systems for all types of users. Furthermore, we highlight a holistic view that can guide the future development and design of Telemedicine systems, enhancing the user experience of both patients and healthcare providers. This research effort suggests the need for system
作者: 心胸開闊    時間: 2025-3-29 02:25

作者: doxazosin    時間: 2025-3-29 03:44
Smart Management of Telemedicine Rooms in an e-Hospital Emergency Departmentms like Genetic and Memetic algorithms. This concept’s potential implementation requires extensive use of concepts like the Internet of Things (IoT), achieving an e-Hospital with a smart management system. This work most significant results were the Emergency Department service quality maximization
作者: 六個才偏離    時間: 2025-3-29 09:22

作者: 睨視    時間: 2025-3-29 11:28
IoT for Enhanced Decision-Making in Medical Information Systems: A Systematic Reviews from 2017 to 2021 using search strategies. IEEE Xplore and PubMed are included for database search. Around 272 papers were selected from searching strategies. While reviewing the title of those papers, filtration was applied, and some papers were removed. Among all papers, only 73 journal articles
作者: nonradioactive    時間: 2025-3-29 19:17
From the Internet of Things to an Internet of Services in Healthcare For this purpose, we use various data transmission techniques appropriate to the respective situation. On the one hand, all tools in this toolbox had to be interconnected in a mesh so that the ever-increasing data streams from the various implants, wearables, and POCTs can not only be technically m
作者: malign    時間: 2025-3-29 21:37

作者: MOT    時間: 2025-3-30 02:32

作者: 總    時間: 2025-3-30 04:18
MIoT-Based Big Data Analytics Architecture, Opportunities and Challenges for Enhanced Telemedicine Sata, however, would not be productive without analytical capacity. Countless of Big Data Analytics approaches have allowed people to gain useful insight into extensive MIoT-based devices produced data. Yet, these resolutions are still in their initial stages, and the realm does not have a wide-rangi
作者: 調(diào)味品    時間: 2025-3-30 12:15

作者: 無表情    時間: 2025-3-30 13:20

作者: 用肘    時間: 2025-3-30 16:43

作者: Fluctuate    時間: 2025-3-31 00:27
Disease Prediction Using Artificial Intelligence: A Case Study on Epileptic Seizure Predictiontion and detection approach based on deep learning is also presented. Since Deep Learning can automatically extract and learn features, the electroencephalography (EEG) time series are fed into the deep learning model. Deep Learning has been utilized in the prediction and detection of epileptic seiz
作者: 高射炮    時間: 2025-3-31 02:43
A Novel Wrapper-Based Feature Selection for Heart Failure Prediction Using an Adaptive Particle Swarport Vector Machine (SVM), Decision Tree (DT), K–Nearest Neighbor, Na?ve Bayesian Classifier (NBC), Random Forest (RF), and Logistic Regression (LR). The results of our method show not only that much fewer features are needed, but also higher accuracy can be accomplished, 81% for Adaptive Particle S
作者: Parameter    時間: 2025-3-31 06:15

作者: neuron    時間: 2025-3-31 11:21

作者: insincerity    時間: 2025-3-31 14:13

作者: bonnet    時間: 2025-3-31 20:55





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