01034nam0 22002651i 450 UON0033849120231205104249.11020091015d1967 |0itac50 bagerDE|||| 1||||Gesammelte Werke in acht Bänden. 2.:Stücke 2]Bertolt Brecht[hrsg. von Elisabeth Hauptmann]Frankfurt am MainSuhrkampc1967P. 910-210521 cm.DEFrankfurt am MainUONL003175832Letteratura drammatica tedesca21BRECHTBertoltUONV11426836137HAUPTMANNElisabethUONV190920SuhrkampUONV260759650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00338491SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI TED 25 I BRE 16 SI ST 3489 5 16 Gesammelte Werke in acht Bänden100490UNIOR03119nam 22005775 450 991102197110332120250828130208.03-031-94898-X10.1007/978-3-031-94898-5(MiAaPQ)EBC32274028(Au-PeEL)EBL32274028(CKB)40430609900041(DE-He213)978-3-031-94898-5(EXLCZ)994043060990004120250828d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierProceedings of 17th International Conference on Machine Learning and Computing ICMLC2025, Volume 2 /edited by Lin Huang, David Greenhalgh1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (1054 pages)Lecture Notes in Networks and Systems,2367-3389 ;14763-031-94897-1 Image Feature Analysis and Processing Technology -- Intelligent Detection Models and Algorithms -- Multimodal Image Intelligent Recognition and Calculation -- Image Segmentation and Classification -- Signal Recognition and Key Technologies -- Information Security Detection and Analysis -- Text Analysis and Classification.This book comprises original and peer reviewed research papers presented at 2025 17th International Conference on Machine Learning and Computing that was held in Guangzhou, China, from February 14 to 17, 2025. The focus of the conference is to establish an effective platform for institutions and industries to share ideas and to present the works of scientists, engineers, educators and students from all over the world. Topics discussed in this volume include Machine Learning Theory and Algorithms, High-performance Computing Models and Data Processing, Large-scale Language Models and Natural Language Processing, Data-oriented Information System Optimization and Intelligent Computing, AI-based Intelligent Control Systems and System Security, etc. The book will become a valuable resource for academics, industry professionals, and engineers working in the related fields of machine learning and computing.Lecture Notes in Networks and Systems,2367-3389 ;1476Computational intelligenceEngineeringData processingMachine learningComputational IntelligenceData EngineeringMachine LearningComputational intelligence.EngineeringData processing.Machine learning.Computational Intelligence.Data Engineering.Machine Learning.006.3Huang Lin665389Greenhalgh David1844454MiAaPQMiAaPQMiAaPQBOOK9911021971103321Proceedings of 17th International Conference on Machine Learning and Computing4427111UNINA06292nam 2200829Ia 450 991014413020332120250930151238.01-118-69337-X1-281-83141-797866118314170-470-72533-80-470-02276-0(CKB)1000000000554532(EBL)366766(SSID)ssj0000231206(PQKBManifestationID)11193962(PQKBTitleCode)TC0000231206(PQKBWorkID)10198697(PQKB)10792870(MiAaPQ)EBC366766(MiAaPQ)EBC4523989(OCoLC)264615432(EXLCZ)99100000000055453220080118d2008 uy 0engur|n|---|||||txtccrQuantitative methods for health research a practical interactive guide to epidemiology and statistics /Nigel Bruce, Daniel Pope and Debbi StanistreetChichester, West Sussex ;Hoboken, NJ J. Wileyc20081 online resource (xiii, 538 pages) illustrationsDescription based upon print version of record.Print version: Bruce, Nigel, 1956- Quantitative methods for health research. Chichester, England ; Hoboken, NJ : John Wiley & Sons, ©2008 0470022744 0470022752 (DLC) 2008002734 (OCoLC)191732328 0-470-02275-2 0-470-02274-4 Includes bibliographical references and index.Quantitative Methods for Health Research; Contents; Preface; 1 Philosophy of science and introduction to epidemiology; Introduction and learning objectives; 1.1 Approaches to scientific research; 1.2 Formulating a research question; 1.3 Rates: incidence and prevalence; 1.4 Concepts of prevention; 1.5 Answers to self-assessment exercises; 2 Routine data sources and descriptive epidemiology; Introduction and learning objectives; 2.1 Routine collection of health information; 2.2 Descriptive epidemiology; 2.3 Information on the environment; 2.4 Displaying, describing and presenting data2.5 Summary of routinely available data2.6 Descriptive epidemiology in action; 2.7 Overview of epidemiological study designs; 2.8 Answers to self-assessment exercises; 3 Standardisation; Introduction and learning objectives; 3.1 Health inequalities in Merseyside; 3.2 Indirect standardisation: calculation of the standardised mortality ratio (SMR); 3.3 Direct standardisation; 3.4 Standardisation for factors other than age; 3.5 Answers to self-assessment exercises; 4 Surveys; Introduction and learning objectives; 4.1 Purpose and context; 4.2 Sampling methods; 4.3 The sampling frame4.4 Sampling error, confidence intervals and sample size4.5 Response; 4.6 Measurement; 4.7 Data types and presentation; 4.8 Answers to self-assessment exercises; 5 Cohort studies; Introduction and learning objectives; 5.1 Why do a cohort study?; 5.2 Obtaining the sample; 5.3 Measurement; 5.4 Follow-up; 5.5 Basic presentation and analysis of results; 5.6 How large should a cohort study be?; 5.7 Confounding; 5.8 Simple linear regression; 5.9 Introduction to multiple linear regression; 5.10 Answers to self-assessment exercises; 6 Case-control studies; Introduction and learning objectives6.1 Why do a case-control study?6.2 Key elements of study design; 6.3 Basic unmatched and matched analysis; 6.4 Sample size for a case-control study; 6.5 Confounding and logistic regression; 6.6 Answers to self-assessment exercises; 7 Intervention studies; Introduction and learning objectives; 7.1 Why do an intervention study?; 7.2 Key elements of intervention study design; 7.3 The analysis of intervention studies; 7.4 Testing more complex interventions; 7.5 How big should the trial be?; 7.6 Further aspects of intervention study design and analysis; 7.7 Answers to self-assessment exercises8 Life tables, survival analysis and Cox regressionIntroduction and learning objectives; 8.1 Survival analysis; 8.2 Cox regression; 8.3 Current life tables; 8.4 Answers to self-assessment exercises; 9 Systematic reviews and meta-analysis; Introduction and learning objectives; 9.1 The why and how of systematic reviews; 9.2 The methodology of meta-analysis; 9.3 Systematic reviews and meta-analyses of observational studies; 9.4 The Cochrane Collaboration; 9.5 Answers to self-assessment exercises; 10 Prevention strategies and evaluation of screening; 10.1 Concepts of risk10.2 Strategies of preventionQuantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community. Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts. The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and aMedicineResearchMethodologyHealthResearchMethodologyEpidemiologyResearchMethodologyEpidemiologyEpidemiologic Methods(DNLM)D004812Biomedical Researchmethods(DNLM)D035843Q000379Biometrymethods(DNLM)D001699Q000379Epidemiology(DNLM)D004813MedicineResearchMethodology.HealthResearchMethodology.EpidemiologyResearchMethodology.Epidemiology.Epidemiologic MethodsBiomedical ResearchmethodsBiometrymethodsEpidemiology362.1072/4610.72Bruce Nigel1956-949543Pope Daniel1969-949544Stanistreet Debbi1963-949545MiAaPQMiAaPQMiAaPQBOOK9910144130203321Quantitative methods for health research2146245UNINA