LEADER 01340nam 2200373 450 001 9910219966103321 005 20230808194314.0 010 $a0-8330-9623-0 035 $a(CKB)3710000000761927 035 $a(WaSeSS)IndRDA00120501 035 $a(EXLCZ)993710000000761927 100 $a20200602d2016 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAssessing the role of state and local public health in outreach and enrollment for expanded coverage $ea case study on New Orleans, Louisiana /$fMalcolm V. Williams [and three others] 210 1$aSanta Monica, California :$cRAND Corporation,$d2016. 215 $a1 online resource (12 pages) 606 $aHealth care reform 606 $aHealth care reform$zLouisiana$zNew Orleans 606 $aPublic health administration$zLouisiana$zNew Orleans 615 0$aHealth care reform. 615 0$aHealth care reform 615 0$aPublic health administration 676 $a362.10425 700 $aWilliams$b Malcolm V.$01266490 801 0$bWaSeSS 801 1$bWaSeSS 906 $aBOOK 912 $a9910219966103321 996 $aAssessing the role of state and local public health in outreach and enrollment for expanded coverage$92973890 997 $aUNINA LEADER 05881nam 22007455 450 001 9910682586103321 005 20251225205225.0 010 $a9783031258916 010 $a3031258916 024 7 $a10.1007/978-3-031-25891-6 035 $a(MiAaPQ)EBC7211994 035 $a(Au-PeEL)EBL7211994 035 $a(CKB)26257779900041 035 $a(DE-He213)978-3-031-25891-6 035 $a(PPN)269092498 035 $a(EXLCZ)9926257779900041 100 $a20230309d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning, Optimization, and Data Science $e8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18?22, 2022, Revised Selected Papers, Part II /$fedited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos Pardalos, Giuseppe Di Fatta, Giovanni Giuffrida, Renato Umeton 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (605 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13811 311 08$aPrint version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science Cham : Springer International Publishing AG,c2023 9783031258909 327 $aExplainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence -- Detection of Morality in Tweets based on the Moral Foundation Theory -- Matrix completion for the prediction of yearly country and industry-level CO2 emissions -- A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0 -- A Matrix Factorization-based Drug-virus Link Prediction Method for SARS CoV -- Drug Prioritization -- Hyperbolic Graph Codebooks -- A Kernel-Based Multilayer Perceptron Framework to Identify Pathways Related to Cancer Stages -- Loss Function with Memory for Trustworthiness Threshold Learning: Case of Face and Facial Expression Recognition -- Machine learning approaches for predicting Crystal Systems: a brief review and a case study -- LS-PON: a Prediction-based Local Search for Neural Architecture Search -- Local optimisation of Nystrm samples through stochastic gradient descent -- Explainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence. 330 $aThis two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13811 606 $aInformation technology$xManagement 606 $aComputer networks 606 $aElectronic digital computers$xEvaluation 606 $aComputer systems 606 $aArtificial intelligence 606 $aMachine learning 606 $aComputer Application in Administrative Data Processing 606 $aComputer Communication Networks 606 $aSystem Performance and Evaluation 606 $aComputer System Implementation 606 $aArtificial Intelligence 606 $aMachine Learning 615 0$aInformation technology$xManagement. 615 0$aComputer networks. 615 0$aElectronic digital computers$xEvaluation. 615 0$aComputer systems. 615 0$aArtificial intelligence. 615 0$aMachine learning. 615 14$aComputer Application in Administrative Data Processing. 615 24$aComputer Communication Networks. 615 24$aSystem Performance and Evaluation. 615 24$aComputer System Implementation. 615 24$aArtificial Intelligence. 615 24$aMachine Learning. 676 $a060.68 676 $a006.31 702 $aNicosia$b Giuseppe 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910682586103321 996 $aMachine learning, optimization, and data science$91949690 997 $aUNINA