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[null,"1.","Record Nr.",null,"UNISA990005847360203316"]
[null,null,"Titolo",null,"I processi ai comunisti italiani in Unione Sovietica, 1930-1940"]
[null,null,"Pubbl/distr/stampa",null,"Firenze : Ponte alle Grazie"]
[null,null,"Descrizione fisica",null,"volumi ; 23 cm"]
[null,null,"Disciplina",null,"324.245075092"]
[null,null,"Soggetti",null,"Comunisti italiani -- Processi -- Unione sovietica -- 1930-1940"]
[null,null,"Collocazione",null,"X.3.B. 6834/"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910464836703321"]
[null,null,"Autore",null,"Linoff Gordon S"]
[null,null,"Titolo",null,"Data mining techniques [[electronic resource] ] : for marketing, sales, and customer relationship management / / Gordon S. Linoff, Michael J.A. Berry"]
[null,null,"Pubbl/distr/stampa",null,"Indianapolis, Ind., : Wiley Pub., Inc., 2011"]
[null,null,"ISBN",null,"1-280-68619-7"]
[{"$nulls":4},"9786613663139"]
[{"$nulls":4},"1-118-08745-3"]
[{"$nulls":4},"1-118-08750-X"]
[null,null,"Edizione",null,"[3rd ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (889 p.)"]
[null,null,"Disciplina",null,"658.802"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Marketing - Data processing"]
[{"$nulls":4},"Business - Data processing"]
[{"$nulls":4},"Electronic books."]
[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","Berry's name appears first on the 2nd ed."]
[{"$nulls":4},"Includes index."]
[null,null,"Nota di contenuto",null,"Data Mining Techniques; Contents; Introduction; Chapter 1 What Is Data Mining and Why Do It?; What Is Data Mining?; Data Mining Is a Business Process; Large Amounts of Data; Meaningful Patterns and Rules; Data Mining and Customer Relationship Management; Why Now?; Data Is Being Produced; Data Is Being Warehoused; Computing Power Is Affordable; Interest in Customer Relationship Management Is Strong; Every Business Is a Service Business; Information Is a Product; Commercial Data Mining Software Products Have Become Available; Skills for the Data Miner; The Virtuous Cycle of Data Mining"]
[{"$nulls":4},"A Case Study in Business Data Mining Identifying B of A's Business Challenge; Applying Data Mining; Acting on the Results; Measuring the Effects of Data Mining; Steps of the Virtuous Cycle; Identify Business Opportunities; Transform Data into Information; Act on the Information; Measure the Results; Data Mining in the Context of the Virtuous Cycle; Lessons Learned; Chapter 2 Data Mining Applications in Marketing and Customer Relationship Management; Two Customer Lifecycles; The Customer's Lifecycle; The Customer Lifecycle; Subscription Relationships versus Event-Based Relationships"]
[{"$nulls":4},"Event-Based Relationships Subscription-Based Relationships; Organize Business Processes Around the Customer Lifecycle; Customer Acquisition; Who Are the Prospects?; When Is a Customer Acquired?; What Is the Role of Data Mining?; Customer Activation; Customer Relationship Management; Winback; Data Mining Applications for Customer Acquisition; Identifying Good Prospects; Choosing a Communication Channel; Picking Appropriate Messages; A Data Mining Example: Choosing the Right Place to Advertise; Who Fits the Profile?; Measuring Fitness for Groups of Readers"]
[{"$nulls":4},"Data Mining to Improve Direct Marketing Campaigns Response Modeling; Optimizing Response for a Fixed Budget; Optimizing Campaign Profitability; Reaching the People Most Influenced by the Message; Using Current Customers to Learn About Prospects; Start Tracking Customers Before They Become \"Customers\"; Gather Information from New Customers; Acquisition-Time Variables Can Predict Future Outcomes; Data Mining Applications for Customer Relationship Management; Matching Campaigns to Customers; Reducing Exposure to Credit Risk; Predicting Who Will Default; Improving Collections"]
[{"$nulls":4},"Determining Customer Value Cross-selling, Up-selling, and Making Recommendations; Finding the Right Time for an Offer; Making Recommendations; Retention; Recognizing Attrition; Why Attrition Matters; Different Kinds of Attrition; Different Kinds of Attrition Model; Predicting Who Will Leave; Predicting How Long Customers Will Stay; Beyond the Customer Lifecycle; Lessons Learned; Chapter 3 The Data Mining Process; What Can Go Wrong?; Learning Things That Aren't True; Patterns May Not Represent Any Underlying Rule; The Model Set May Not Reflect the Relevant Population"]
[{"$nulls":4},"Data May Be at the Wrong Level of Detail"]
[null,null,null,"Sommario/riassunto","The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990's, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised—is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more Provides best practices for performing data mining using simple tools such as Excel Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results."]
[null,"3.","Record Nr.",null,"UNINA9910337526503321"]
[null,null,"Titolo",null,"Abdominal Wall Surgery : How Reimbursement Systems Can Change Surgical Evolution / / edited by Dalila Patrizia Greco, Elio Borgonovi"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019"]
[null,null,"ISBN",null,"3-030-02426-1"]
[null,null,"Edizione",null,"[1st ed. 2019.]"]
[null,null,"Descrizione fisica",null,"1 online resource (234 pages)"]
[null,null,"Disciplina",null,"617.55059"]
[null,null,"Soggetti",null,"Surgery"]
[{"$nulls":4},"Health services administration"]
[{"$nulls":4},"Medical economics"]
[{"$nulls":4},"Health Care Management"]
[{"$nulls":4},"Health Economics"]
[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,"PART I: Abdominal wall -- 1 Epidemiology -- 2 Anatomy -- 3 Clusters of patology & interventions -- 4 Unit of wall surgery -- 5 Organization and certification of abdominal wall surgery: the German example, the easter Europe example, the Sweden example, the Spain example -- 6 Organization and certification of abdominal wall surgery: the Eastern Europe example -- 7 Organization and certification of abdominal wall surgery: the Swedish example -- 8 Organization and certification of abdominal wall surgery: the Spanish example -- 9 Devices and biomaterials: from chemistry to certification -- 10 Assistential settings -- 11 Preventing incisional hernias: closure of abdominal wall, follow-up in abdominal surgery -- PART II: Economics -- 12 Economic Evaluation and Health Technology Assessment of Healthcare Programmes -- 13 Comparative Effectiveness in Health Technology Assessment for Medical Devices -- 14 Economic evaluation of abdominal Wall Surgery (cost benefit analysis, cost effectiveness, cost-quality analysis) -- 15 Cost Containement: abdominal surgery unit -- 16 The Shouldice experience -- 17 Presurgical hidden costs: imaging, assessment clinic -- 18 Postsurgical hidden costs: neuralgia -- 19 Postsurgical hidden costs: infection -- 20 Reimbursement strategies for medical devices: the case of Abdominal Wall Surgery in Italy -- 21 Economic modelling and Budget Impact Analysis in Abdominal Surgery: "]
[{"$nulls":4},"the case of mesh -- PART III: Outcome -- 22 How to measure outcome in surgery -- 23 Present and future of EBM -- 24 Registries: monitoring clinical ourcomes -- 25 Registries as a source of information for the purchase of devices -- PART IV: Future perspectives -- 26 Stakeholders opinions -- 27 Evolution of abdominal wall surgery in non developed countries -- 28 How social patterns affect the development of science -- 29 Ferrying to the future."]
[null,null,null,"Sommario/riassunto","This book presents different patient-oriented perspectives from surgeons, economic evaluation and management researchers, and business companies active in the healthcare sector, striking a balance between the appropriateness/effectiveness of treatment and efficiency/cost. It does not include technical surgical details, but instead provides the necessary knowledge regarding different groups of patients to help economic and management researchers make accurate evaluations. Although partially based on the specific case of abdominal wall surgery in the Italian health system, the book defines a model that can, with the necessary adaptations, be applied in other national contexts. It also analyzes different reimbursement systems and methods of data collection. This approach supports the evolution form evidence-based medicine (EBM) to the future of real-world data (big data analysis). Further, it highlights the critical issue of “silos” reimbursement, which is the pillar of DRG, and proposes methodology to evaluate the direct and indirect benefit and costs of surgery (for example quality of care, costs incurred in cases of surgical complications due to the use of inappropriate, low-cost material or due to surgical procedure. It is a valuable resource for clinicians, surgeons, policymakers and managers in the field."]