標(biāo)題: Titlebook: Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes; Shashi Kant Gupta,Dimitrios A. Karras,Rajesh Natar Book [打印本頁] 作者: energy 時間: 2025-3-21 18:50
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書目名稱Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes讀者反饋學(xué)科排名
作者: 積極詞匯 時間: 2025-3-21 21:50
Natesh Mahadev,Anitha Premkumar,V. L. Sowmya,Rajesh Natarajanoordination (in time) can be viewed as essentially decoupled. Path following for each vehicle is formulated in terms of driving a conveniently defined generalized error vector to zero; vehicle coordination is achieved by adjusting the speed of each vehicle along its particular path, based on informa作者: 完成才會征服 時間: 2025-3-22 02:32
K. Krishna Sowjanya,K. P. Bindu Madaviing analysis and compromise choice exploration do not arrive at a consensus, a facility is provided to create a sublated choice among those provided by them. The trial experimental results confirmed that permissive meeting analysis and compromise choice exploration are sufficiently useful for derivi作者: 豎琴 時間: 2025-3-22 08:29 作者: GREEN 時間: 2025-3-22 09:04 作者: ORE 時間: 2025-3-22 13:31 作者: nocturnal 時間: 2025-3-22 18:13 作者: municipality 時間: 2025-3-22 21:40 作者: creditor 時間: 2025-3-23 04:18
C. D. Divyan and colleagues. One example is medical research support on rare diseases which raises the need for data sharing across multiple health organizations (not necessarily being fond of each other) in a fully transparent, fraud-resistant research process while preserving best-possible privacy of patient作者: patella 時間: 2025-3-23 08:58
Aparna Vajpayeen and colleagues. One example is medical research support on rare diseases which raises the need for data sharing across multiple health organizations (not necessarily being fond of each other) in a fully transparent, fraud-resistant research process while preserving best-possible privacy of patient作者: 敵意 時間: 2025-3-23 11:16
K. P. Bindu Madavi,K. Krishna Sowjanyanships; (iii) task-based coordination; and (iv) information technology support, which together identified the needs of collaborative disaster response coordination. Using evidence from the data, these factors were related to one another to develop a framework for context-aware multi-party coordinati作者: 離開就切除 時間: 2025-3-23 14:01
Aarti Sangwannships; (iii) task-based coordination; and (iv) information technology support, which together identified the needs of collaborative disaster response coordination. Using evidence from the data, these factors were related to one another to develop a framework for context-aware multi-party coordinati作者: 使增至最大 時間: 2025-3-23 20:41
3004-958X rs overseeing this volume’s creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology...Our aim is to enco978-3-031-65024-6978-3-031-65022-2Series ISSN 3004-958X Series E-ISSN 3004-9598 作者: 彩色的蠟筆 時間: 2025-3-23 23:09
Patient Health Services for Early Detection Therapy of Diabetes Mellitus with Expert System and IOTds accompanied by healing therapy and treatment methods. This system was created so that sufferers can understand and understand the types of diabetes mellitus along with healing therapies and how to treat them. This system provides several disease prevention solutions according to the type of disea作者: POINT 時間: 2025-3-24 02:51
Integrating IoT and AI in Healthcare: A Novel MS-GNN Framework for Disease Diagnosis,“accuracy, sensitivity, specificity, and AUC (Area under the Curve)” for?heart disease, diabetes, and thyroid datasets. Based on experimental results, the proposed approach attained 95.87, 95.36, and 90.45% accuracy on three different datasets. The results highlight the potential of AI?and IoT?in sm作者: aviator 時間: 2025-3-24 07:18
Advancing Glioblastoma Treatment Through AI-Driven Radiomics: A Comparative Study of Feature Selecteighbour, Quadratic Discriminant Analysis, and Multi-layer Perceptron, among others. The main objective is to identify the most powerful combinations that improve the capacity to forecast accurately and reliably, therefore making a significant contribution to the advancement of personalised medical 作者: cringe 時間: 2025-3-24 10:59
Artificial Intelligence in Personalized Health Services for Better Patient Care,els. By taking into consideration the fact that each patient responds differently to treatments, this not only increases the efficacy of medical interventions but also reduces their negative consequences. The chapter also covers how artificial intelligence can expedite diagnostic procedures. Artific作者: 消瘦 時間: 2025-3-24 18:21 作者: CLASP 時間: 2025-3-24 21:25
Machine Learning-Based Autism Spectrum Disorder Prediction: A Comparative Approach,s the efficacy of ML techniques in prediction of Autism Spectrum Disorder (ASD). Notably, the study finds that Random Forest and Extra Tree models exhibit high precision in test outcomes. This underscores the promising potential of ML methodologies in accurately predicting ASD. The research methodol作者: medium 時間: 2025-3-25 01:09
Preventive Health Care System for Early Heart Disease Detection Using IoT and Machine Learning,icient in analyzing large volumes of data. A Preventive health care framework is proposed in this paper to predict early heart disease by procuring data such as Heart Rate (HT), Systolic Blood pressure (SBP), and Diastolic blood pressure (DBP) from wearable IoT Devices. The same data is analyzed usi作者: 細查 時間: 2025-3-25 04:56 作者: 在前面 時間: 2025-3-25 10:45 作者: Canvas 時間: 2025-3-25 14:02
Unlocking the Potential: Biometric Traits in Healthcare with a Focus on Eye Diseases,rds securely. Voice recognition can also be used to control medical equipment, such as ventilators or infusion pumps, gaining popularity in healthcare. Facial recognition can be used to identify patients and healthcare providers, and it can also be used to monitor patients for signs of distress or t作者: incontinence 時間: 2025-3-25 17:10
Pixels, Perspectives, and Psychological Strain: Unravelling the Link Between Negative Body Image, Iedia literacy initiatives to workplace wellness and mental health support systems. The study advocates for ongoing research and collaboration with technology companies to develop innovative, real-time solutions. The implications of negative body image on social and work adjustment, as evidenced by t作者: 環(huán)形 時間: 2025-3-25 22:10 作者: MORT 時間: 2025-3-26 02:00
Book 2024ents the potentials offered by AI and IoT is both captivating and revolutionary...As editors overseeing this volume’s creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology...Our aim is to enco作者: RODE 時間: 2025-3-26 06:09 作者: 著名 時間: 2025-3-26 09:15 作者: 兵團 時間: 2025-3-26 12:44 作者: colostrum 時間: 2025-3-26 19:14
V. T. Venkateswarlu,P. Manimozhi,R. Janani,K. V. Subbarao,S. Tamilselvan,G. Ganesh Kumar作者: faultfinder 時間: 2025-3-26 22:22 作者: 善于騙人 時間: 2025-3-27 04:35
Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes作者: FEIGN 時間: 2025-3-27 06:08
Shashi Kant Gupta,Dimitrios A. Karras,Rajesh NatarDemonstrates how to unlock the potential of AI and IoT to revolutionize healthcare for the betterment of patients.Provides an exploration of the possibilities of AI and IoT in the field of healthcare.作者: PATHY 時間: 2025-3-27 12:35
Information Systems Engineering and Managementhttp://image.papertrans.cn/r/image/829917.jpg作者: 河流 時間: 2025-3-27 14:31 作者: STRIA 時間: 2025-3-27 19:37
978-3-031-65024-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: Climate 時間: 2025-3-28 00:18
Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes978-3-031-65022-2Series ISSN 3004-958X Series E-ISSN 3004-9598 作者: 一致性 時間: 2025-3-28 02:32 作者: Digest 時間: 2025-3-28 06:49
DNA-Based Secure Image Transmission Framework Using Encryption and LSB Steganography,od. Before transmission to the intended user, DWT (Discrete Wavelet Transform) compression is employed to ensure effective transfer and reduce file size. Once received, the reverse approach effectively extracts the concealed data.作者: 無底 時間: 2025-3-28 11:11
Book 2024n...The healthcare sector is currently experiencing a shift fueled by technological advancements and a heightened focus on providing tailored, efficient and impactful care to individuals. AI and IoT have emerged as facilitators of this evolution presenting opportunities to elevate patient results st作者: dandruff 時間: 2025-3-28 17:57 作者: HARD 時間: 2025-3-28 22:38 作者: CANT 時間: 2025-3-29 01:55 作者: custody 時間: 2025-3-29 05:07 作者: STRIA 時間: 2025-3-29 10:57 作者: hazard 時間: 2025-3-29 15:24
Exploring AI and IoT Integration for Medicine Recommendation with Chimp Optimized Dynamic XGBoost (lood pressure and cholesterol levels. Machine learning algorithms can evaluate real-time data from heart disease patients to prescribe individualized drug regimens using IoT-enabled healthcare technologies. These algorithms ensure accurate and flexible treatment regimens by taking lifestyle characte作者: lactic 時間: 2025-3-29 16:44
Integrating IoT and AI in Healthcare: A Novel MS-GNN Framework for Disease Diagnosis,a, while the AI suggests insights for decision-making after processing and analyzing the gathered data. The convergence of IoT?with?AI?presents numerous potential applications in healthcare. This research introduces a novel framework for disease diagnosis in intelligent healthcare systems called Mon作者: anniversary 時間: 2025-3-29 21:04
Advancing Glioblastoma Treatment Through AI-Driven Radiomics: A Comparative Study of Feature Selectrequent incidence, need advanced diagnostic techniques for effective treatment. Radiomics is a crucial approach in this field that utilises quantitative analysis of medical pictures. This work conducts a comprehensive comparative assessment of several techniques for selecting relevant features and m作者: adjacent 時間: 2025-3-30 00:03 作者: Prologue 時間: 2025-3-30 06:02
Artificial Intelligence in Personalized Health Services for Better Patient Care,ions to each patient‘s unique traits is essential in the era of precision medicine to improve patient outcomes. The chapter explores how artificial intelligence technologies, through their analysis of large datasets to identify distinctive patterns and trends in patient health, contribute to this pa作者: 債務(wù) 時間: 2025-3-30 10:23
Transforming Healthcare: The Synergistic Fusion of AI and IoT for Intelligent, Personalized Well-Betunities to enhance patient care, improve diagnostic accuracy, and optimize operational efficiency. AI contributes to diagnostic precision through image analysis, predictive analytics, and personalized medicine, while IoT facilitates real-time data collection through wearable devices, remote patient作者: CRACK 時間: 2025-3-30 14:14
Machine Learning-Based Autism Spectrum Disorder Prediction: A Comparative Approach,opments in machine learning (ML) offer an exciting chance to enhance ASD prediction, transforming the diagnostic and management processes. This research paper implements an exhaustive examination of ML-based ASD prediction methods, emphasizing a comparative assessment of various ML algorithms and fe作者: averse 時間: 2025-3-30 16:52 作者: BOOR 時間: 2025-3-30 20:55
Preventive Health Care System for Early Heart Disease Detection Using IoT and Machine Learning, regularly thereby preventing the disease from developing further. Continuous monitoring of the patient‘s condition is carried out effectively by using the technology of Sensor/IoT Devices. IoT devices for health care come under the emerging technology Internet of Medical Things (IoMT). The IoMT usa作者: commonsense 時間: 2025-3-31 02:08 作者: NORM 時間: 2025-3-31 06:34
AI Innovations in Health Care: Reshaping Diagnostics and Care,is of the various ways in which AI is transforming the industry, particularly in regards to their role in transforming diagnostic and care methods. AI technologies have brought about a new era, drastically changing the way that various allied health sector’s function. This chapter delves into the ke作者: 翅膀拍動 時間: 2025-3-31 11:22 作者: PET-scan 時間: 2025-3-31 14:12
An Approach to Pattern Prediction and Early Recognition of Lung Cancer Employing Machine Learning Ted diagnosis. By creating and implementing a novel machine learning architecture intended for early lung cancer diagnosis, our work aims to address this problem. To do this, an extensive dataset including a broad spectrum of health-related attributes is utilised. These include age, gender, lifestyle作者: 賞心悅目 時間: 2025-3-31 20:52 作者: Fibrinogen 時間: 2025-3-31 23:50
Pixels, Perspectives, and Psychological Strain: Unravelling the Link Between Negative Body Image, In social and work adjustment. Leveraging a combination of traditional survey methods and cutting-edge IoT technologies, the research provides a nuanced understanding of the complexities surrounding body image perceptions. The findings reveal a consistent trend of females experiencing higher levels o作者: 長矛 時間: 2025-4-1 04:09 作者: 機警 時間: 2025-4-1 08:09
