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P278Validation of HMPAO-Tc-99m as a myocardial perfusion radiotracer: preliminary results

European Heart Journal - Cardiovascular Imaging 2019年第SUPPLEMENT_3期20卷

作者： Faria, M T Oliveira, A Vilas-Boas, M C Maia, P M Rego, R Sousa, J Pereira, J Cunha, J P S Rocha-Goncalves, F Martins, E Centro Hospitalar Universitário de São João E.P.E. Nuclear Medicine Department Porto Portugal Institute for Systems Engineering and Computers - Technology and Science (INESC TEC) FEUP Porto Portugal Centro Hospitalar Universitário de São João E.P.E. Neurophysiology Unit Neurology Department Porto Portugal Centro Hospitalar Universitário de São João E.P.E. Angiology and Vascular Surgery Department Porto Portugal Faculty of Medicine University of Porto Medicine Department Porto Portugal

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CINDERELLA Trial: validation of an artificial-intelligence cloud-based platform to improve the shared decision-making process and outcomes in breast cancer patients proposed for locoregional treatment

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European Journal of Surgical Oncology 2024年第2期50卷 107916-107916页

作者： Bonci, Eduard-Alexandru Kaidar-Person, Orit Antunes, Marilia Ciani, Oriana Cruz, Helena Di Micco, Rosa Gentilini, Oreste Gouveia, Pedro Heil, Jörg Kabata, Pawel Freitas, Nuno Gonçalves, Tiago Romariz, Miguel Martins, Henrique Mavioso, Carlos Mika, Martin Pfob, André Schinköthe, Timo Silva, Giovani Cardoso, Maria-João Champalimaud Foundation Champalimaud Research and Clinical Centre Lisbon Portugal Iuliu Hatieganu University of Medicine and Pharmacy Surgical Oncology and Gynecologic Oncology Department Cluj-Napoca Romania Sheba Medical Center Breast Cancer Radiation Therapy Unit Ramat Gan Israel Tel-Aviv University Sackler School of Medicine Tel-Aviv Israel University of Lisbon Faculty of Sciences Lisbon Portugal University of Lisbon Instituto Superior Técnico Lisbon Portugal SDA Bocconi University Center for Research on Health and Social Care Management Milan Italy San Raffaele University and Research Hospital Breast Surgery Unit Milan Italy University of Lisbon Faculty of Medicine Lisbon Portugal Heidelberg University Hospital Department of Obstetrics & Gynecology Heidelberg Germany Medical University of Gdańsk Faculty of Medicine - Department of Surgical Oncology Gdańsk Poland INESC TEC - Institute for Systems and Computer Engineering- Technology and Science Networked Intelligent Systems Porto Portugal University of Porto Faculty of Sciences Porto Portugal University of Porto Faculty of Engineering Porto Portugal ISCTE - University Institute of Lisbon Social and Enterprise Sciences Lisbon Portugal CANKADO GmbH Ottobrunn Germany

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108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions

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ESMO Open 2024年 9卷 103179-103179页

作者： A. Pfob E-A. Bonci O. Kaidar-Person M. Antunes O. Ciani H. Cruz R. Di Micco O.D. Gentilini J. Heil P. Kabata M. Romariz T. Gonçalves H.G. Martins L. Borsoi M. Mika N. Romem T. Schinköthe G. Silva M. Bobowicz M.J. Cardoso Department of Obstetrics & Gynecology Heidelberg University Hospital Heidelberg Germany Breast Unit Champalimaud Research and Clinical Centre Champalimaud Foundation Lisbon Portugal Breast Cancer Radiation Therapy Unit Sheba Medical Center Ramat Gan Israel CEAUL - Centro de Estatística e Aplicações Faculdade de Ciências Universidade de Lisboa Lisbon Portugal Center for Research on Health and Social Care Management (CERGAS) SDA Bocconi University Milan Italy Breast Surgery Unit San Raffaele University and Research Hospital Milan Italy Department of General Surgery Copernicus Mamma Centrum Wojewodzkie Centrum Onkologii Copernicus Podmiot Leczniczy Gdańsk Poland Telecommunications and Multimedia INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal ISCTE - Instituto Universitário de Lisboa Lisbon Portugal CANKADO GmbH Ottobrunn Germany Surgical Oncology Medical University of Gdansk Gdansk Poland

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Forecasting: theory and practice

arXiv

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arXiv 2020年

作者： Petropoulos, Fotios Apiletti, Daniele Assimakopoulos, Vassilios Babai, Mohamed Zied Barrow, Devon K. Taieb, Souhaib Ben Bergmeir, Christoph Bessa, Ricardo J. Bijak, Jakub Boylan, John E. Browell, Jethro Carnevale, Claudio Castle, Jennifer L. Cirillo, Pasquale Clements, Michael P. Cordeiro, Clara Oliveira, Fernando Luiz Cyrino de Baets, Shari Dokumentov, Alexander Ellison, Joanne Fiszeder, Piotr Franses, Philip Hans Frazier, David T. Gilliland, Michael Gönül, M. Sinan Goodwin, Paul Grossi, Luigi Grushka-Cockayne, Yael Guidolin, Mariangela Guidolin, Massimo Gunter, Ulrich Guo, Xiaojia Guseo, Renato Harvey, Nigel Hendry, David F. Hollyman, Ross Januschowski, Tim Jeon, Jooyoung Jose, Victor Richmond R. Kang, Yanfei Koehler, Anne B. Kolassa, Stephan Kourentzes, Nikolaos Leva, Sonia Li, Feng Litsiou, Konstantia Makridakis, Spyros Martin, Gael M. Martinez, Andrew B. Meeran, Sheik Modis, Theodore Nikolopoulos, Konstantinos Önkal, Dilek Paccagnini, Alessia Panagiotelis, Anastasios Panapakidis, Ioannis Pavía, Jose M. Pedio, Manuela Pedregal, Diego J. Pinson, Pierre Ramos, Patrícia Rapach, David E. Reade, J. James Rostami-Tabar, Bahman Rubaszek, Michal Sermpinis, Georgios Shang, Han Lin Spiliotis, Evangelos Syntetos, Aris A. Talagala, Priyanga Dilini Talagala, Thiyanga S. Tashman, Len Thomakos, Dimitrios Thorarinsdottir, Thordis Todini, Ezio Arenas, Juan Ramón Trapero Wang, Xiaoqian Winkler, Robert L. Yusupova, Alisa Ziel, Florian School of Management University of Bath United Kingdom Politecnico di Torino Turin Italy Forecasting and Strategy Unit School of Electrical and Computer Engineering National Technical University of Athens Greece Kedge Business School France Department of Management Birmingham Business School University of Birmingham United Kingdom Belgium Faculty of Information Technology Monash University Melbourne Australia INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Social Statistics and Demography University of Southampton United Kingdom Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University United Kingdom School of Mathematics and Statistics University of Glasgow United Kingdom Department of Mechanical and Industrial Engineering University of Brescia Italy Magdalen College University of Oxford United Kingdom ZHAW School of Management and Law Zurich University of Applied Sciences Switzerland ICMA Centre Henley Business School University of Reading United Kingdom Faculdade de Ciências e Tecnologia Universidade do Algarve Portugal CEAUL Faculdade de Ciências Universidade de Lisboa Portugal Brazil Department of Business Informatics and Operations Management Faculty of Economics and Business Administration Universiteit Gent Belgium Let’s Forecast Australia Faculty of Economic Sciences and Management Nicolaus Copernicus University in Torun Poland Econometric Institute Erasmus School of Economics Rotterdam Netherlands Department of Econometrics and Business Statistics Monash University Melbourne Australia SAS United States Newcastle Business School Northumbria University Newcastle upon Tyne United Kingdom Department of Statistical Sciences University of Padua Italy Darden School of Business University of Virginia United States Finance Department Bocconi University Baffi-CAREFIN Centre Milan Italy Department of Tourism and Service Management MODUL Un

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. © 2020, CC BY.

关键词： Forecasting

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