Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Mattia Fornasa"'
Autor:
Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Adam Kantorik, Tom de Ruijter, Willem E. Herter, Martijn Beudel, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W. G. Elbers, the Dutch ICU Data Sharing Against Covid-19 Collaborators
Publikováno v:
Critical Care, Vol 25, Iss 1, Pp 1-10 (2021)
Abstract Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granula
Externí odkaz:
https://doaj.org/article/c04ef1ea0f0b493fb77ba8e33296e30c
Autor:
Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn-Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cina, Martijn Beudel, Willem E. Herter, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W. G. Elbers
Publikováno v:
Critical Care, Vol 25, Iss 1, Pp 1-12 (2021)
Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential
Externí odkaz:
https://doaj.org/article/fda39d22c4e340efbc3a04cd3073f6b4
Autor:
Lucas M. Fleuren, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Tariq A. Dam, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Nardo J. M. van der Meer, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Sefanja Achterberg, Harald J. Faber, A. Karakus, Menno Beukema, Robert Entjes, Paul de Jong, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Martijn Beudel, Nicolet F. de Keizer, Mark Hoogendoorn, Armand R. J. Girbes, Willem E. Herter, Paul W. G. Elbers, Patrick J. Thoral, Dutch ICU Data Sharing Against COVID-19 Collaborators
Publikováno v:
Intensive Care Medicine Experimental, Vol 9, Iss 1, Pp 1-15 (2021)
Abstract Background The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies
Externí odkaz:
https://doaj.org/article/02fac2c9c60242bebdd4de7e0fafb6d2
Autor:
Tariq A. Dam, MD, Harm-Jan de Grooth, MD, PhD, Thomas Klausch, PhD, Lucas M. Fleuren, MD, Daan P. de Bruin, MSc, Robert Entjes, MD, Thijs C. D. Rettig, MD, PhD, Dave A. Dongelmans, MD, PhD, Age D. Boelens, MD, Sander Rigter, MD, Stefaan H. A. Hendriks, MD, Remko de Jong, MD, Marlijn J. A Kamps, MD, Marco Peters, MD, A. Karakus, MD, Diederik Gommers, MD, PhD, Dharmanand Ramnarain, MD, Evert-Jan Wils, MD, PhD, Sefanja Achterberg, MD, PhD, Ralph Nowitzky, MD, Walter van den Tempel, MD, Cornelis P. C. de Jager, MD, PhD, Fleur G. C. A. Nooteboom, MD, Evelien Oostdijk, MD, PhD, Peter Koetsier, MD, Alexander D. Cornet, MD, PhD, FRCP, Auke C. Reidinga, MD, Wouter de Ruijter, MD, PhD, Rob J. Bosman, MD, Tim Frenzel, MD, PhD, Louise C. Urlings-Strop, MD, PhD, Paul de Jong, MD, Ellen G. M. Smit, MD, Olaf L. Cremer, MD, PhD, D. Jannet Mehagnoul-Schipper, MD, PhD, Harald J. Faber, MD, Judith Lens, MD, Gert B. Brunnekreef, MD, Barbara Festen-Spanjer, MD, Tom Dormans, MD, PhD, Annemieke Dijkstra, MD, Bram Simons, MD, A. A. Rijkeboer, MD, Sesmu Arbous, MD, PhD, Marcel Aries, MD, PhD, Menno Beukema, MD, Daniël Pretorius, MD, Rutger van Raalte, MD, Martijn van Tellingen, MD, EDIC, Niels C. Gritters van den Oever, MD, Robbert C. A. Lalisang, MD, Michele Tonutti, MRes, Armand R. J. Girbes, MD, PhD, EDIC, Mark Hoogendoorn, PhD, Patrick J. Thoral, MD, EDIC, Paul W. G. Elbers, MD, PhD, EDIC, on behalf of the Dutch ICU Data Sharing Against COVID-19 Collaborators, Remko van den Akker, Tom A. Rijpstra, M. C. Reuland, Klaas Sierk Arnold, Arend Jan Meinders, Nicolas Schroten, Laura van Manen, Leon Montenij, Julia Koeter, J. W. Fijen, Jasper van Bommel, Roy van den Berg, Martha de Bruin, Roger van Rietschote, Ellen van Geest, Koen S. Simons, Anisa Hana, Joost Labout, Michael Kuiper, Albertus Beishuizen, Bart van de Gaauw, Roos Renckens, B. van den Bogaard, Peter Pickkers, Pim van der Heiden, Dennis Geutjes, Claudia (C. W.) van Gemeren, Emma Rademaker, Frits H. M. van Osch, Johan Lutisan, Jacomar J. M. van Koesveld, Bart P. Grady, Martijn de Kruif, Martin E. Haan, Luca Roggeveen, Dagmar M. Ouweneel, Ronald Driessen, Jan Peppink, G. J. Zijlstra, A. J. van Tienhoven, Evelien van der Heiden, Jan Jaap Spijkstra, Hans van der Spoel, Angelique de Man, Heder J. de Vries, Fuda van Diggelen, Ali el Hassouni, David Romero Guzman, Sandjai Bhulai, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Adam Izdebski, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Willem E. Herter, Michael de Neree tot Babberich, Olivier Thijssens, Lot Wagemakers, Hilde G. A. van der Pol, Tom Hendriks, Julie Berend, Virginia Ceni Silva, Robert F. J. Kullberg, Leo Heunks, Nicole Juffermans, Arjen J. C. Slooter, Martijn Beudel, Nicolet F. de Keizer
Publikováno v:
Critical Care Explorations, Vol 3, Iss 10, p e0555 (2021)
OBJECTIVES:. As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive m
Externí odkaz:
https://doaj.org/article/32f239460e134af0a3cea6a1b4ef0a1c
Autor:
Patrick J. Thoral, MD, Mattia Fornasa, PhD, Daan P. de Bruin, MSc, Michele Tonutti, MRes, Hidde Hovenkamp, MSc, Ronald H. Driessen, Armand R. J. Girbes, MD, PhD, Mark Hoogendoorn, PhD, Paul W. G. Elbers, MD, PhD
Publikováno v:
Critical Care Explorations, Vol 3, Iss 9, p e0529 (2021)
Objectives:. Unexpected ICU readmission is associated with longer length of stay and increased mortality. To prevent ICU readmission and death after ICU discharge, our team of intensivists and data scientists aimed to use AmsterdamUMCdb to develop an
Externí odkaz:
https://doaj.org/article/8a0a2ea2cb5e4db094ce4edc87399592
Autor:
Laurenske A. Visser, Juliette de Vos, Giovanni Cinà, Mattia Fornasa, Paul W. G. Elbers, Aletta A. de Beer, Patrick Thoral
Publikováno v:
Value in Health, 25(3), 359-367. Elsevier Ltd.
de Vos, J, Visser, L A, de Beer, A A, Fornasa, M, Thoral, P J, Elbers, P W G & Cinà, G 2022, ' The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge ', Value in Health, vol. 25, no. 3, pp. 359-367 . https://doi.org/10.1016/j.jval.2021.06.018
Value in Health, 25(3), 359-367. Elsevier Limited
Value in health, 25(3), 359-367. Elsevier Limited
de Vos, J, Visser, L A, de Beer, A A, Fornasa, M, Thoral, P J, Elbers, P W G & Cinà, G 2022, ' The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge ', Value in Health, vol. 25, no. 3, pp. 359-367 . https://doi.org/10.1016/j.jval.2021.06.018
Value in Health, 25(3), 359-367. Elsevier Limited
Value in health, 25(3), 359-367. Elsevier Limited
Objectives The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given
Autor:
Roberto Noorduijn-Londono, Sander Rigter, Willem E. Herter, Tomas Machado, Gert B. Brunnekreef, Thijs C. D. Rettig, Evert-Jan Wils, Remko de Jong, S Arbous, Harald J. Faber, Cornelis P.C. de Jager, Paul de Jong, Auke C Reidinga, Sebastiaan J. J. Vonk, Dave A. Dongelmans, Wouter de Ruijter, Taco Houwert, Ralph Nowitzky, Daan P de Bruin, Robert Entjes, Diederik Gommers, Dharmanand Ramnarain, Marlijn J A Kamps, Mark Hoogendoorn, Evelien A. N. Oostdijk, Martijn G. Scholtemeijer, Age D Boelens, Armand R. J. Girbes, Fleur G C A Nooteboom, Barbara Festen-Spanjer, Peter Koetsier, Giovanni Cinà, Hidde Hovenkamp, Sefanja Achterberg, Ellen G M Smit, Robbert C. A. Lalisang, D Jannet Mehagnoul-Schipper, Rob J. Bosman, Patrick Thoral, Judith Lens, Tariq A Dam, Olaf L. Cremer, Lucas M. Fleuren, Martijn Beudel, Paul W. G. Elbers, Tom Dormans, Aletta A. de Beer, Marco Peters, Alexander D. Cornet, Tim Frenzel, Louise C Urlings-Strop, Michele Tonutti, Mattia Fornasa, Walter van den Tempel, Davide Quintarelli, A Karakus, Stefaan H A Hendriks
Publikováno v:
Critical Care, 25(1):304. Springer Science + Business Media
Critical Care, 25, 1
Critical Care, 25(1):304. BioMed Central Ltd.
Critical Care, 25(1). BMC
Fleuren, L M, Dam, T A, Tonutti, M, de Bruin, D P, Lalisang, R C A, Gommers, D, Cremer, O L, Bosman, R J, Rigter, S, Wils, E-J, Frenzel, T, Dongelmans, D A, de Jong, R, Peters, M, Kamps, M J A, Ramnarain, D, Nowitzky, R, Nooteboom, F G C A, de Ruijter, W, Urlings-Strop, L C, Smit, E G M, Mehagnoul-Schipper, D J, Dormans, T, de Jager, C P C, Hendriks, S H A, Achterberg, S, Oostdijk, E, Reidinga, A C, Festen-Spanjer, B, Brunnekreef, G B, Cornet, A D, van den Tempel, W, Boelens, A D, Koetsier, P, Lens, J, Faber, H J, Karakus, A, Entjes, R, de Jong, P, Rettig, T C D, Arbous, S, Vonk, S J J, Fornasa, M, Machado, T, Houwert, T, Hovenkamp, H, Noorduijn-Londono, R, Quintarelli, D, Scholtemeijer, M G, de Beer, A A, Cina, G, Beudel, M, Herter, W E, Girbes, A R J, Hoogendoorn, M, Thoral, P J & Elbers, P W G 2021, ' The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients ', Critical Care, vol. 25, no. 1, 304 . https://doi.org/10.1186/s13054-021-03733-z
Critical Care, 25
Critical Care, Vol 25, Iss 1, Pp 1-12 (2021)
Critical Care
Critical Care, 25, 1
Critical Care, 25(1):304. BioMed Central Ltd.
Critical Care, 25(1). BMC
Fleuren, L M, Dam, T A, Tonutti, M, de Bruin, D P, Lalisang, R C A, Gommers, D, Cremer, O L, Bosman, R J, Rigter, S, Wils, E-J, Frenzel, T, Dongelmans, D A, de Jong, R, Peters, M, Kamps, M J A, Ramnarain, D, Nowitzky, R, Nooteboom, F G C A, de Ruijter, W, Urlings-Strop, L C, Smit, E G M, Mehagnoul-Schipper, D J, Dormans, T, de Jager, C P C, Hendriks, S H A, Achterberg, S, Oostdijk, E, Reidinga, A C, Festen-Spanjer, B, Brunnekreef, G B, Cornet, A D, van den Tempel, W, Boelens, A D, Koetsier, P, Lens, J, Faber, H J, Karakus, A, Entjes, R, de Jong, P, Rettig, T C D, Arbous, S, Vonk, S J J, Fornasa, M, Machado, T, Houwert, T, Hovenkamp, H, Noorduijn-Londono, R, Quintarelli, D, Scholtemeijer, M G, de Beer, A A, Cina, G, Beudel, M, Herter, W E, Girbes, A R J, Hoogendoorn, M, Thoral, P J & Elbers, P W G 2021, ' The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients ', Critical Care, vol. 25, no. 1, 304 . https://doi.org/10.1186/s13054-021-03733-z
Critical Care, 25
Critical Care, Vol 25, Iss 1, Pp 1-12 (2021)
Critical Care
Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0198612e3328f981d56e307c22225b4
https://research.vu.nl/en/publications/41a31196-39ef-40c7-bbc7-24d6f90b170f
https://research.vu.nl/en/publications/41a31196-39ef-40c7-bbc7-24d6f90b170f
Autor:
Hidde Hovenkamp, Patrick Thoral, Michele Tonutti, Ronald H. Driessen, Armand R. J. Girbes, Daan P de Bruin, Paul W. G. Elbers, Mark Hoogendoorn, Mattia Fornasa
Publikováno v:
Critical care explorations, 3(9). Lippincott Williams and Wilkins
Critical Care Explorations, Vol 3, Iss 9, p e0529 (2021)
Critical Care Explorations
Thoral, P J, Fornasa, M, de Bruin, D P, Tonutti, M, Hovenkamp, H, Driessen, R H, Girbes, A R J, Hoogendoorn, M & Elbers, P W G 2021, ' Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support : Uniting Intensivists and Data Scientists ', Critical care explorations, vol. 3, no. 9, pp. e0529 . https://doi.org/10.1097/CCE.0000000000000529
Critical Care Explorations, Vol 3, Iss 9, p e0529 (2021)
Critical Care Explorations
Thoral, P J, Fornasa, M, de Bruin, D P, Tonutti, M, Hovenkamp, H, Driessen, R H, Girbes, A R J, Hoogendoorn, M & Elbers, P W G 2021, ' Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support : Uniting Intensivists and Data Scientists ', Critical care explorations, vol. 3, no. 9, pp. e0529 . https://doi.org/10.1097/CCE.0000000000000529
Unexpected ICU readmission is associated with longer length of stay and increased mortality. To prevent ICU readmission and death after ICU discharge, our team of intensivists and data scientists aimed to use AmsterdamUMCdb to develop an explainable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1c3dc42e489a1ed2c46e40c6b83c0e5
https://research.vumc.nl/en/publications/aac7812b-95d4-435a-91a0-47f02d74c55b
https://research.vumc.nl/en/publications/aac7812b-95d4-435a-91a0-47f02d74c55b
Autor:
Patrick J. Thoral, Mattia Fornasa, Daan P. de Bruin, Hidde Hovenkamp, Ronald H. Driessen, Armand R.J. Girbes, Mark Hoogendoorn, Paul W.G. Elbers
Background Unexpected ICU readmission is associated with longer length of stay and an increase in mortality. Real time support systems could prevent untimely discharge from the ICU. We aim to develop a machine learning model for implementation at the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7f15ea561fb472854a2baf23e41f6e2
https://doi.org/10.21203/rs.2.21940/v1
https://doi.org/10.21203/rs.2.21940/v1
Autor:
Mattia Fornasa, Fabio Zandanel, Thomas H. Reiprich, Anatoly Klypin, Florian Pacaud, Francisco Prada
Publikováno v:
Digital.CSIC. Repositorio Institucional del CSIC
instname
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Cosmological simulations are fundamental tools to study structure formation and the astrophysics of evolving structures, in particular clusters of galaxies. While hydrodynamical simulations cannot sample efficiently large volumes and explore differen