Title |
Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort
|
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Published in |
Critical Care, August 2021
|
DOI | 10.1186/s13054-021-03720-4 |
Pubmed ID | |
Authors |
Harry Magunia, Simone Lederer, Raphael Verbuecheln, Bryant Joseph Gilot, Michael Koeppen, Helene A. Haeberle, Valbona Mirakaj, Pascal Hofmann, Gernot Marx, Johannes Bickenbach, Boris Nohe, Michael Lay, Claudia Spies, Andreas Edel, Fridtjof Schiefenhövel, Tim Rahmel, Christian Putensen, Timur Sellmann, Thea Koch, Timo Brandenburger, Detlef Kindgen-Milles, Thorsten Brenner, Marc Berger, Kai Zacharowski, Elisabeth Adam, Matthias Posch, Onnen Moerer, Christian S. Scheer, Daniel Sedding, Markus A. Weigand, Falk Fichtner, Carla Nau, Florian Prätsch, Thomas Wiesmann, Christian Koch, Gerhard Schneider, Tobias Lahmer, Andreas Straub, Andreas Meiser, Manfred Weiss, Bettina Jungwirth, Frank Wappler, Patrick Meybohm, Johannes Herrmann, Nisar Malek, Oliver Kohlbacher, Stephanie Biergans, Peter Rosenberger |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | 11% |
France | 1 | 5% |
Colombia | 1 | 5% |
Belgium | 1 | 5% |
United Kingdom | 1 | 5% |
Malaysia | 1 | 5% |
Unknown | 12 | 63% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 15 | 79% |
Practitioners (doctors, other healthcare professionals) | 2 | 11% |
Scientists | 1 | 5% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 102 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 13 | 13% |
Student > Ph. D. Student | 10 | 10% |
Student > Bachelor | 10 | 10% |
Student > Master | 6 | 6% |
Student > Doctoral Student | 6 | 6% |
Other | 17 | 17% |
Unknown | 40 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 21 | 21% |
Engineering | 10 | 10% |
Nursing and Health Professions | 6 | 6% |
Computer Science | 5 | 5% |
Economics, Econometrics and Finance | 3 | 3% |
Other | 15 | 15% |
Unknown | 42 | 41% |