Zobrazeno 1 - 10
of 1 169
pro vyhledávání: '"Seibold, H."'
Autor:
Peter Rinab
Publikováno v:
WIRTSCHAFTSINFORMATIK. 49:69-70
Publikováno v:
Animal Biodiversity and Conservation, Vol 37, Iss 1, Pp 77-88 (2014)
Understanding the role of scavengers in ecosystems is important for species conservation and wildlife management. We used road–killed animals, 15 in summer 2003 (June–August) and nine in winter 2003/2004 (from November to January), to test the fo
Externí odkaz:
https://doaj.org/article/83d8bdd22f704c18890a3792d361c2d3
Autor:
Reeve K; Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland., On BI; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany., Havla J; lnstitute of Clinical Neuroimmunology, Ludwig-Maximilians-Universität München, Munich, Germany., Burns J; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.; Pettenkofer School of Public Health, Munich, Germany., Gosteli-Peter MA; University Library, University of Zurich, Zurich, Switzerland., Alabsawi A; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany., Alayash Z; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.; Institute of Health Services Research in Dentistry, University of Münster, Muenster, Germany., Götschi A; Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland., Seibold H; IGDORE, Munich, Germany., Mansmann U; Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.; Pettenkofer School of Public Health, Munich, Germany., Held U; Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zurich, Switzerland.
Publikováno v:
The Cochrane database of systematic reviews [Cochrane Database Syst Rev] 2023 Sep 08; Vol. 9. Cochrane AN: CD013606. Date of Electronic Publication: 2023 Sep 08.
Akademický článek
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Publikováno v:
Radiation Research, 1979 Jul 01. 79(1), 149-161.
Externí odkaz:
https://www.jstor.org/stable/3575028
Autor:
Seibold, H. R., Thorson, Ralph E.
Publikováno v:
The Journal of Parasitology, 1955 Jun 01. 41(3), 285-288.
Externí odkaz:
https://www.jstor.org/stable/3274207
Autor:
Seibold, H. R.
Publikováno v:
Avian Diseases, 1965 Nov 01. 9(4), 570-578.
Externí odkaz:
https://www.jstor.org/stable/1588140
Publikováno v:
Proceedings of the first Teaching Machine Learning and Artificial Intelligence Workshop at ECML-PKDD 2020, 14.09.2020, virtuell, virtuellVolume 141: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, http://proceedings.mlr.press/v141/
Faced by the abundant use of machine learning in industry and academia, the effective and efficient teaching of core concepts in this field becomes of high importance. For this, we organized a workshop on teaching methods in the field of machine lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______4577::56d549dbf75cc08b66b79b729423df26
https://www.hzdr.de/publications/Publ-32481-1
https://www.hzdr.de/publications/Publ-32481-1
Autor:
Saller T; Department of Anaesthesiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany; Scientific Commission on Gerontoanaesthesiology, German Association for Anaesthesiology and Intensive Care Medicine, Roritzer Str. 19, 90419 Nuremberg, Germany. Electronic address: tsaller@med.lmu.de., Hubig L; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany., Seibold H; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany., Schroeder Z; Department of Anaesthesiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany., Wang B; Department of Anaesthesiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany., Groene P; Department of Anaesthesiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany., Perneczky R; Department of Psychiatry, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; German Center for Neurodegenerative Disorders (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Strasse 17, 81377 Munich, Germany; Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, Level 2 Faculty Building South Kensington Campus, London SW7 2AZ, UK; Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, 385A Glossop Road, Sheffield S10 2HQ, UK., von Dossow V; Scientific Commission on Gerontoanaesthesiology, German Association for Anaesthesiology and Intensive Care Medicine, Roritzer Str. 19, 90419 Nuremberg, Germany; Institute for Anesthesiology, Heart and Diabetes Center NRW, Ruhr University of Bochum, Georgstr. 11, 32545 Bad Oeynhausen, Germany., Hinske LC; Department of Anaesthesiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany; Professorship for Data Management und Clinical Decision Support, Faculty of Medicine, Augsburg University, University Hospital, Stenglinstr. 2, 86156 Augsburg, Germany.
Publikováno v:
Journal of clinical anesthesia [J Clin Anesth] 2022 Dec; Vol. 83, pp. 110957. Date of Electronic Publication: 2022 Sep 06.
Autor:
Casalicchio, G., Bossek, J., Lang, M., Kirchhoff, D., Kerschke, P., Hofner, B., Seibold, H., Joaquin Vanschoren, Bischl, B.
Publikováno v:
Technische Universität Dortmund
arXiv. Cornell University Library
ISSUE=1701.01293;TITLE=arXiv
Pure TUe
arXiv. Cornell University Library
ISSUE=1701.01293;TITLE=arXiv
Pure TUe
OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interfac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::49a7ddee3df674cc7b1905790f38cccf
https://www.zora.uzh.ch/id/eprint/130579/
https://www.zora.uzh.ch/id/eprint/130579/