LEADER 04407nam 22006135 450 001 9910918697503321 005 20241221115226.0 010 $a9783031752049$b(electronic bk.) 010 $z9783031752032 024 7 $a10.1007/978-3-031-75204-9 035 $a(MiAaPQ)EBC31855540 035 $a(Au-PeEL)EBL31855540 035 $a(CKB)37065136800041 035 $a(DE-He213)978-3-031-75204-9 035 $a(OCoLC)1492949783 035 $a(EXLCZ)9937065136800041 100 $a20241221d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSocial Network Analysis and Mining Applications in Healthcare and Anomaly Detection /$fedited by Mehmet Kaya, Sleiman Alhajj, Kashfia Sailunaz, Min-Yuh Day 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (338 pages) 225 1 $aLecture Notes in Social Networks,$x2190-5436 311 08$aPrint version: Kaya, Mehmet Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection Cham : Springer,c2025 9783031752032 327 $aSensitivity to Noise in Features in Graph Neural Network Learning -- Interpretable Ensemble Model For Associative Classification -- Scalable Algorithms to Measure User Influence in Social Networks Detecting Comorbidity Using Machine Learning -- Detecting Comorbidity Using Machine Learning -- Evaluating the Effectiveness of Mitigative and Preventative Actions on Viral Spread In A Small Community Using An Agent-based Stochastic Simulation -- Evaluating the Effectiveness of Mitigative and Preventative Actions on Viral Spread In A Small Community Using An Agent-based Stochastic Simulation -- Predicting Donor Behavior using the Dynamics of Event Co-Attendance Networks Analyzing the impact of COVID-19 on Portuguese Social Media -- Analyzing the impact of COVID-19 on Portuguese Social Media -- SegSkin: An Effective Application for Skin Lesion Segmentation using Attention-Based VGG-UNet -- Segmentation and Classification of Dermoscopic Skin Images using U-Net and Handcrafted Features -- Global Prevalence Patterns of Anti-Asian Prejudice on Twitter During the COVID-19 Pandemic -- Enhancing fraud detection in SWIFT financial systems through Ontology-Based knowledge integration and Graph-Driven analysis -- A study of firm-switching of inventors in Big Tech using public patent data -- Measuring the Echo-chamber Phenomenon Through Exposure Bias. 330 $aThis book is an excellent source of knowledge for readers interested in the latest developments in social network analysis and mining, particularly with applications in healthcare and anomaly detection. It covers topics such as sensitivity to noise in features, enhancing fraud detection in financial systems, measuring the echo-chamber phenomenon, detecting comorbidity, and evaluating the effectiveness of mitigative and preventative actions on viral spread in small communities using agent-based stochastic simulations. Additionally, it discusses predicting behavior, measuring and identifying influence, analyzing the impact of COVID-19 on various social aspects, and using UNet for handling various skin conditions. This book helps readers develop their own perspectives on adapting social network concepts to various applications. It also demonstrates how to use various machine learning techniques for tackling challenges in social network analysis and mining. 410 0$aLecture Notes in Social Networks,$x2190-5436 606 $aMachine learning 606 $aSocial media 606 $aMedical informatics 606 $aMachine Learning 606 $aSocial Media 606 $aHealth Informatics 615 0$aMachine learning. 615 0$aSocial media. 615 0$aMedical informatics. 615 14$aMachine Learning. 615 24$aSocial Media. 615 24$aHealth Informatics. 676 $a006.31 700 $aKaya$b Mehmet$01781203 701 $aAlhajj$b Sleiman$01781204 701 $aSailunaz$b Kashfia$01781205 701 $aDay$b Min-Yuh$01781206 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910918697503321 996 $aSocial Network Analysis and Mining Applications in Healthcare and Anomaly Detection$94305961 997 $aUNINA LEADER 04142nam 22005415 450 001 9911003593103321 005 20250519131156.0 010 $a3-031-90478-8 024 7 $a10.1007/978-3-031-90478-3 035 $a(CKB)38859210300041 035 $a(DE-He213)978-3-031-90478-3 035 $a(MiAaPQ)EBC32125196 035 $a(Au-PeEL)EBL32125196 035 $a(EXLCZ)9938859210300041 100 $a20250519d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProceedings of 5th International Conference on Artificial Intelligence and Smart Energy $eICAIS 2025, Volume 1 /$fedited by S. Manoharan, Alexandru Tugui, Isidoros Perikos 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (XIII, 585 p. 279 illus., 227 illus. in color.) 225 1 $aInformation Systems Engineering and Management,$x3004-9598 ;$v41 311 08$a3-031-90477-X 327 $aDeep Learning for Fake News Detection: A Review of Multi-Model Approaches In Social Media Contexts -- A Comprehensive Survey on Text Spotting in Natural Images Using Deep Learning -- A Review on Transfer Learning Models for Precise Alzheimer's Disease Stage Identification -- A Review of Artificial Intelligence Techniques in Papaya Leaf Disease Classification -- A study of Graph Neural Network Frameworks and Frontiers -- Avian Census: Real-Time Bird Counting using Region-based Convolutional Neural Network -- Implementation of Fuzzy Optimization in Activity Recognition with deep learning -- ALO-FCE: An Antlion Optimization Based Feature Extraction For Network Traffic Classification Using Fully Connected Autoencoders -- Transforming images into multilingual captions for accessibility and interaction -- ResNet-Defake: Detecting Deepfake Images with Customized ResNet -- AI Driven Food Recognition and Real-Time Pose Estimation for Health Monitoring -- Ensemble-Based DL Model For Predicting And Detecting Diabetic Retinopathy Using Retinal Images -- Leveraging Supervised Learning Algorithms for Automated and Accurate Cattle Disease Diagnosis in Livestock Farming in Somalia -- Video Forgery Detection Using Multi-Scale Feature Extraction with ResNet50 -- Smartoutfit: CNN Based Matching for Perfect Outfit Combination. 330 $aThis book discusses the latest developments in computing techniques that power smart energy and sustainable solutions. Over the last few years, artificial intelligence (AI) has been more deeply embedded in our lives, revolutionizing industries and communication. Intelligent computing models are now transforming traditional energy applications in this digital age through smart automation, optimization, and adaptation. The book addresses major facets of intelligent computing and communication technologies, such as intelligent data analysis, predictive modeling, optimization, neural networks, AI, machine learning, deep learning, and the Internet of Things (IoT). All these technologies are discussed in practical applications, e.g., smart cities and smart industries, their transformative possibilities. 410 0$aInformation Systems Engineering and Management,$x3004-9598 ;$v41 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a006.3 702 $aManoharan$b S$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTugui$b Alexandru$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPerikos$b Isidoros$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911003593103321 996 $aProceedings of 5th International Conference on Artificial Intelligence and Smart Energy$94381095 997 $aUNINA