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[null,"1.","Record Nr.",null,"UNINA9910918595103321"]
[null,null,"Autore",null,"Cleophas Ton J"]
[null,null,"Titolo",null,"Application of Regularized Regressions to Identify Novel Predictors in Clinical Research / / by Ton J. Cleophas, Aeilko H. Zwinderman"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9783031722479"]
[{"$nulls":4},"3031722477"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (274 pages)"]
[null,null,"Disciplina",null,"610"]
[null,null,"Soggetti",null,"Medical sciences"]
[{"$nulls":4},"Statistics"]
[{"$nulls":4},"Health Sciences"]
[{"$nulls":4},"Applied Statistics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Basic Principles of Regression Analysis.  -- Optimal Scaling, Discretization, and Regularization vs Traditional Linear Regression.  -- Regularized Regression Analysis, Ridge, Lasso, Elastic Net Regression Coefficients.  -- Effect of Predictors on Health Scores, 110 Patients, Traditional vs Regularized Regressions.  -- Effect on Physical strength of Races, 60 Patients, Traditional Regression vs Regularized regressions.  -- Effects of Genetic Polymorphisms on Clinical Outcomes, 250 Patients, Traditional vs Regularized Regressions.  -- Effect of Old Treatment and Age on New Treatment, 35 Patients, Traditional vs Regularized Regressions.  -- Effect on Paroxysmal Atrial Fibrillations of Four Predictors, 50 Patients, Traditional vs Regularized Regressions.  -- Effect of Air Quality of Operating Rooms on Infections, 8 Operating Rooms, Traditional vs Regularized Regressions.  -- Effect on Weightloss of Age, Calorieintake, Exercise, Interaction, 64 Patients, Traditional vs Regularized Regressions.  -- Effect on Body Surface Measured of Gender, Age, Weight, Height, and Weight x Height Interaction, 90 Patients, Traditional vs Regularized Regressions.  -- Effect on Paroxysmal Atrial Fibrillations of Gender, Treatment and Their Interaction, 40 Patients, Traditional vs Regularized Regressions.  -- Effect on Hours of Sleep of Treatment Group, Age, Gender, Comorbidity, 20 Patients, Traditional vs Regularized Regressions.  -- Effect of Betaagonist and Prednisone on Peak Expiratory Flow, 78 COPD "]
[{"$nulls":4},"Patients, Traditional vs Regularized Regressions.  -- Effect on LDL Cholesterol Reduction of Five Predictors, 953 Patients, Traditional vs Regularized Regressions.  -- Effect of Five Factors on Body Weight, 217 Patients, Traditional vs Regularized Regressions.  -- Functional Data Analysis and Regularized Regressions."]
[null,null,null,"Sommario/riassunto","This textbook is an important novel menu for multiple variables regression entitled \"regularized regression\". It is a must have for identifying unidentified leading factors. Also, you get fitted parameters for your overfitted data. Finally, there is no more need for commonly misunderstood p-values. Instead, the regression coefficient, R-value, as reported from a regression line has been applied as the key predictive estimator of the regression study. With simple one by one variable regression it is no wider than -1 to +1. With multiple variables regression it can easily get > +1 or < -1. This means we have a seriously flawed regression model, mostly due to collinearity or non-linear data. Completing the analysis will lead to overfitting, and thus a meaningless significant study due to data spread wider than compatible with random. In order for the regression coefficients to remain in the right size, fortunately a shrinking procedure has been invented. In the past two decades regularized regression has become a major topic of research, particularly with high dimensional data. Yet, the method is pretty new and infrequently used in real-data analysis. Its performance as compared to traditional null hypothesis testing has to be confirmed by prospective comparisons. Most studies published to date are of a theoretical nature involving statistical modeling and simulation studies. The journals Nature and Science published 19 and 10 papers of this sort in the past 8 years. The current edition will for the first time systematically test regularized regression against traditional regression analysis in 20 clinical data examples. The edition is also a textbook and tutorial for medical and healthcare students as well as recollection bench and help desk for professionals. Each chapter can be studied as a standalone, and, using, real as well as hypothesized data, it tests the performance of the novel methodology against traditional regressions. Step by step analyses of 20 data files are included for self-assessment. The authors are well qualified in their field. Professor Zwinderman is past-president of the International Society of Biostatistics and Professor Cleophas is past-president of the American College of Angiology. The authors have been working together for 25 years and their research can be characterized as a continued effort to demonstrate that clinical data analysis is a discipline at the interface of biology and mathematics."]
[null,"2.","Record Nr.",null,"UNINA9910409993903321"]
[null,null,"Autore",null,"Willman Joshua M"]
[null,null,"Titolo",null,"Beginning PyQt : A Hands-on Approach to GUI Programming / / by Joshua M. Willman"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020"]
[null,null,"ISBN",null,"9781484258576"]
[{"$nulls":4},"1484258576"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (449 pages)"]
[null,null,"Disciplina",null,"005.43"]
[null,null,"Soggetti",null,"Python (Computer program language)"]
[{"$nulls":4},"Programming languages (Electronic computers)"]
[{"$nulls":4},"Open source software"]
[{"$nulls":4},"Computer programming"]
[{"$nulls":4},"Python"]
[{"$nulls":4},"Programming Languages, Compilers, Interpreters"]
[{"$nulls":4},"Open Source"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Chapter 1 - Charting the Course -- Chapter 2 - Getting Started -- Chapter 3 - Adding Functions Through Buttons -- Chapter 4 - Learning about Layout -- Chapter 5 - Menus, Toolbars,and More  -- Chapter 6 - Styling Your GUIs -- Chapter 7 - Creating GUIs with Qt Designer -- Chapter 8 - Working with the Clipboard -- Chapter 9 - Graphics and Animation in PyQt -- Chapter 10 - Intro to Handling Databases -- Chapter 11 - Asynchronous Programming -- Chapter 12 - Extra Projects -- Appendix A - Reference Guide for PyQt -- Appendix B - Python Refresher."]
[null,null,null,"Sommario/riassunto","Learn GUI application development from the ground up, taking a practical approach by building simple projects that teach the fundamentals of using PyQt. Each chapter gradually moves on to teach more advanced and diverse concepts to aid you in designing interesting applications using the latest version of PyQt. You’ll start by reviewing the beginning steps of GUI development from, using different projects in every chapter to teach new widgets or concepts that will help you to build better UIs. As you follow along, you will construct more elaborate GUIs,covering topics that include storing data using the clipboard, "]
[{"$nulls":4},"graphics and animation, support for SQL databases, and multithreading applications. Using this knowledge, you’ll be able to build a photo editor, games, a text editor, a working web browser and an assortment of other GUIs. Beginning PyQt will guide you through the process of creating UIs to help you bring your own ideas to life. Learn what is necessary to begin making your own applications and more with PyQt! You will: Create your own cross-platform GUIs with PyQt and Python Use PyQt’s many widgets and apply them to building real applications Build larger applications and break the steps into smaller parts for deeper understanding Work with complex applications in PyQt, from animation to databases and more."]
[null,"3.","Record Nr.",null,"UNINA9911018667903321"]
[null,null,"Autore",null,"Cristea Alexandra I"]
[null,null,"Titolo",null,"Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED : 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part III / / edited by Alexandra I. Cristea, Erin Walker, Yu Lu, Olga C. Santos, Seiji Isotani"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"3-031-99267-9"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (540 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 2592"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Database management"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"User interfaces (Computer systems)"]
[{"$nulls":4},"Human-computer interaction"]
[{"$nulls":4},"Education - Data processing"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Database Management"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"User Interfaces and Human Computer Interaction"]
[{"$nulls":4},"Computers and Education"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Late Breaking Results  -- Beyond Detection: Rethinking Education in the Age of AI-writing.  -- Help-Seeking in Problem-Solving: Comparing Generative AI, Peers, and Teacher.  -- How Teacher-Provided Need Support Affects Learning Performance in Human-Computer Collaborative Teaching Environments.  -- Deep Reinforcement Learning for Engagement-Aware Question Selection in Adaptive Assessment Systems.  -- Knowledge, uses and perceptions of ChatGPT in higher education.  -- Inclusive Data Literacy: UDL and AI-Assisted Data "]
[{"$nulls":4},"Storytelling for BVI Students.  -- Virtual Simulated Patients for Medical Interviews Using Large Language Models with a Self-Refinement Mechanism to Suppress Excessive Responses.  -- Playful Pathways to AI Literacy: Designing NLP Activities for Middle School AI Education.  -- Generating Diverse Difficulty Examples in Embedding Vector Spaces via Inverse Embedding.  -- Knowledge Tracing with A Temporal Hypergraph Memory Network.  -- An Augmented Intelligence System for Automated Quality Control and Feedback Generation of Multiple Choice Test Items.  -- ClickSight: Interpreting Student Clickstreams to Reveal Insights on Learning Strategies via LLMs.  -- Effects of Human and Automated Feedback on Preservice Teachers’ Nonverbal Teaching Skills During Microteaching.  -- Avalon: A Human-in-the-Loop LLM Grading System with Instructor Calibration and Student Self Assessment.  -- Empowering Teachers with Technology: A National Study on a Formative Assessment Platform.  -- CASSA: Context-Aware Self-Attention with Global Context Suppression and Relevance Modulation for MCQ Difficulty Estimation.  -- Privacy-Preserved Automated Scoring using Federated Learning for Educational Research.  -- Dude, where’s my utterance? Evaluating the effects of automatic segmentation and transcription on CPS detection.  -- VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback.  -- \"Small Device, Big Decision:\" Comparing Lightweight LLMs’ Computational Performance and Output Quality for AIED Unplugged.  -- Personalized Math Learning for Young Learners: Preliminary Findings from a Rigorous Study of a Game-Based Program.  -- Teachers’ Perspectives on Using and Teaching Artificial Intelligence in Early Primary Education.  -- Automatic Assessment of Spoken English for Uruguayan Spanish L1 Young Learners.  -- Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment.  -- Tutor or Mentor. A Comparative Usability Study of AI Roles in Higher Education.  -- Workshops and Tutorials  -- XAI-Ed: Half-day Workshop on Pedagogy-Founded Explainable AI for Transparent, User-Centered AI in Education.  -- Workshop on Epistemics and Decision-Making in AI-Supported Education.  -- D-SAIL - Transformative Curriculum Design: Digitalisation, Sustainability, and AI Literacy for 21st Century Learning (Half-Day Workshop).  -- Second Workshop on the Automatic Evaluation of Learning and Assessment Content.  -- Human-AI Collaboration and Culture For Equity and Inclusion.  -- Preparing teachers for an equitable AI integration in education (Half-day workshop).  -- AI Literacy For All: 1st International Workshop on AI Literacy Education For All (Half-Day Event).  -- Workshop on Advancements in AI-Supported Exploratory Learning (AI4EL).  -- Applications of Generative AI to Support Teaching and Learning in Higher Education: A Half-Day Workshop.  -- Intelligent Textbooks: The Sixth International Workshop.  -- Full-day Tutorial: Conducting in-the-moment data-driven classroom interviews (DDCI) during digital learning using Quick Red Fox (QRF).  -- Ethical Artificial Intelligence and Education: The need for international regulation to foster human rights, democracy and equity.  -- The Second International Workshop on Multimodal Artificial Intelligence in Education (MAIEd’25).  -- NLP and Generative AI for Language Learning and Assessment: Synergies between Research and Practice.  -- Fair4AIED 2025 – First International Workshop on Fairness in Algorithmic Decision-Making for Education.  -- Multimodal Interactions and Explainable AI for Reflective Physical and Online Learning: miXai^learn Workshop."]
[null,null,null,"Sommario/riassunto","This three-volume set CCIS 2590-2592 constitutes poster papers and late breaking results, workshops and tutorials, practitioners, industry "]
[{"$nulls":4},"and policy track, doctoral consortium, blue sky and wideAIED papers presented at the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22–26, 2025. The 72 full papers and 73 short papers (72 of them presented as posters) presented in this book were carefully reviewed and selected from 296 submissions. They are organized in topical sections as follows: Part I: BlueSky; Practitioners, Industry and Policy; WideAIED; Doctoral Consortium. Part II: Late Breaking Results; Part III: Late Breaking Results; Workshops and Tutorials."]