LEADER 04376nam 22006855 450 001 9911001458303321 005 20250501130210.0 010 $a3-031-88854-5 024 7 $a10.1007/978-3-031-88854-0 035 $a(CKB)38696408000041 035 $a(DE-He213)978-3-031-88854-0 035 $a(MiAaPQ)EBC32068864 035 $a(Au-PeEL)EBL32068864 035 $a(EXLCZ)9938696408000041 100 $a20250501d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplications of Computational Intelligence $e7th IEEE Colombian Conference, ColCACI 2024, Pamplona, Colombia, July 17?19, 2024, Revised Selected Papers /$fedited by Alvaro David Orjuela-Cañón, Jesus A. Lopez, Oscar J. Suarez 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (X, 165 p. 65 illus., 40 illus. in color.) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v2212 311 08$a3-031-88853-7 327 $aOn Using Deep Learning for Automatic Classification System of Microseisms at Cotopaxi Volcano -- Real Time Monitoring of Solar Photovoltaic Power Plants: A Concentrated Validation Study -- Performance tests of LLMs in the context of answers on Industry 4.0 -- Optimal Integration of PV Sources and D STATCOMs in Unbalanced Distribution Networks to Minimize Energy Losses A Master Slave Optimization Approach -- Duolingo evolution: From automation to Artificial Intelligence -- Hybrid SCA IPOPT Approach for the Optimal Location and Sizing of TSCs in Medium Voltage Distribution Networks -- Recognizing Overarching Themes and Actors in Peacebuilding: A Longitudinal Analysis of Press Content in Latin America -- A Comparative Study of Nonlinear PI and PI PBC Control Strategies for Single-Phase PWM CSC Using Adaptive Load Estimation -- A Linear Algebra Based Controller for an Autonomous Ground Vehicle Commissioning and Testing -- Using Machine and Deep Transfer Learning for Classification of EEG Signals from Embodied and Non embodied Priming in a Motor Imagery Training in Virtual Reality -- Solar Irradiance Forecasting based on Neural Networks for Sequential Data Analysis. 330 $aThis book CCIS 2212 constitutes the referred proceedings of the 7th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2024, held in Pamplona, Colombia, during July 17?19, 2024. The 11 full papers were carefully reviewed and selected from 35 submissions. They explore various topics in the area of computational intelligence (CI), such as solar and photovoltaic forecasting, microseismical signal analysis, LLM performance analysis, evolution in translate systems, recognition of actors and peacebuilding, control in autonomous vehicles, and electroencephalography signals analysis. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v2212 606 $aArtificial intelligence 606 $aComputer science$xMathematics 606 $aComputers, Special purpose 606 $aAlgorithms 606 $aEducation$xData processing 606 $aArtificial Intelligence 606 $aMathematics of Computing 606 $aSpecial Purpose and Application-Based Systems 606 $aDesign and Analysis of Algorithms 606 $aComputers and Education 615 0$aArtificial intelligence. 615 0$aComputer science$xMathematics. 615 0$aComputers, Special purpose. 615 0$aAlgorithms. 615 0$aEducation$xData processing. 615 14$aArtificial Intelligence. 615 24$aMathematics of Computing. 615 24$aSpecial Purpose and Application-Based Systems. 615 24$aDesign and Analysis of Algorithms. 615 24$aComputers and Education. 676 $a006.3 702 $aOrjuela-Can?o?n$b Alvaro David$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLo?pez$b Jesu?s A.$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSuarez$b Oscar J$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911001458303321 996 $aApplications of Computational Intelligence$92089766 997 $aUNINA LEADER 06183nam 22007815 450 001 9911031573803321 005 20251001130735.0 010 $a3-031-98728-4 024 7 $a10.1007/978-3-031-98728-1 035 $a(CKB)41521066300041 035 $a(MiAaPQ)EBC32323724 035 $a(Au-PeEL)EBL32323724 035 $a(DE-He213)978-3-031-98728-1 035 $a(OCoLC)1547896775 035 $a(EXLCZ)9941521066300041 100 $a20251001d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning and Deep Learning Modeling and Algorithms with Applications in Medical and Health Care /$fedited by Manoj Diwakar, Vinayakumar Ravi, Prabhishek Singh, Hoang Pham 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (521 pages) 225 1 $aSpringer Series in Reliability Engineering,$x2196-999X 311 08$a3-031-98727-6 327 $aEnhancing dysarthric speech for improved clinical communication: A deep learning approach -- Speech-based real-world scene understanding for assistive care of the visually impaired -- Medical image segmentation with deep learning: An overview -- Lightweight generative model for synthetic biomedical images with enhanced quality -- Pediatric dental disease detection using X-ray image enhancements and deep learning algorithms -- Evaluation of Parkinson disease from MRI images using deep learning techniques -- Analyzing the effect of eyes open and eyes closed states on EEG in Parkinson?s disease with ON and OFF medication -- Automated detection of diabetic retinopathy using ResNet-50 deep learning model -- Deep learning model for decoding subcortical brain activity from simultaneous EEG-FMRI multi-model data -- Secure transmission of medical images in IoMT for smart cities using data hiding scheme -- Deep learning approaches to heart stroke prediction: Model evaluation and insights -- Harnessing predictive modeling techniques for early detection and management of diseases: Challenges, innovations, and future directions -- Fundamentals of machine learning and deep learning for healthcare applications -- Automatic detection of Parkinson disease through various machine learning models -- Transforming healthcare: The role of AI and ML in disease prediction, treatment, and patient satisfaction -- Multi-modality medical (CT, MRI, ultrasound etc.) Image fusion using machine learning/deep learning -- Leveraging digital devices for objective behavioral health assessment: Computational machine learning methods for sleep and mental health evaluation -- Optimizing medical image quality through hybrid machine learning techniques and convolutional denoising autoencoders -- Image segmentation in multimodal medical imaging using deep learning models -- Brain MRI analysis for multiple sclerosis detection using deep learning techniques. 330 $aThis book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications. The book covers among other areas: Image acquisition and formation. Computer-aided diagnosis. Image classification. Feature extraction. Image enhancement/segmentation. Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are: Machine learning and deep learning applications. Medical imaging applications. Feature extraction and analysis. Medical image classification, segmentation, recognition, and registration. Medical image analysis and enhancement.