Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Moons, Karel GM"'
Autor:
Carriero, Alex, Luijken, Kim, de Hond, Anne, Moons, Karel GM, van Calster, Ben, van Smeden, Maarten
Risk prediction models are increasingly used in healthcare to aid in clinical decision making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for model development are ofte
Externí odkaz:
http://arxiv.org/abs/2404.19494
Autor:
Nijman, Steven WJ, Hoogland, Jeroen, Groenhof, T Katrien J, Brandjes, Menno, Jacobs, John JL, Bots, Michiel L, Asselbergs, Folkert W, Moons, Karel GM, Debray, Thomas PA
Use of prediction models is widely recommended by clinical guidelines, but usually requires complete information on all predictors that is not always available in daily practice. We describe two methods for real-time handling of missing predictor val
Externí odkaz:
http://arxiv.org/abs/2012.01099
Autor:
Vollmer, Sebastian, Mateen, Bilal A., Bohner, Gergo, Király, Franz J, Ghani, Rayid, Jonsson, Pall, Cumbers, Sarah, Jonas, Adrian, McAllister, Katherine S. L., Myles, Puja, Granger, David, Birse, Mark, Branson, Richard, Moons, Karel GM, Collins, Gary S, Ioannidis, John P. A., Holmes, Chris, Hemingway, Harry
Machine learning (ML), artificial intelligence (AI) and other modern statistical methods are providing new opportunities to operationalize previously untapped and rapidly growing sources of data for patient benefit. Whilst there is a lot of promising
Externí odkaz:
http://arxiv.org/abs/1812.10404
Autor:
de Hond, Anne, Leeuwenberg, Tuur, Bartels, Richard, van Buchem, Marieke, Kant, Ilse, Moons, Karel GM, van Smeden, Maarten
Publikováno v:
The Lancet Digital Health; July 2024, Vol. 6 Issue: 7 pe441-e443, 3p
Autor:
Damen, Johanna, Reitsma, Johannes B, Van Smeden, Maarten, Kellerhuis, Bas, Schuit, Ewoud, Moons, Karel GM, Hooft, Lotty, Kaul, Tabea, Bada Yang
Background: Multiple tools for assessing the methodological quality of diagnosis and prognosis research exist, with similar scope and overlap in quality items. Which tool should be used for a particular diagnostic or prognostic study type or design i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ab5654895223761e31b0a52671e93da
Autor:
Kengne, Andre Pascal, Beulens, Joline WJ, Peelen, Linda M, Moons, Karel GM, van der Schouw, Yvonne T, Schulze, Matthias B, Spijkerman, Annemieke MW, Griffin, Simon J, Grobbee, Diederick E, Palla, Luigi, Tormo, Maria-Jose, Arriola, Larraitz, Barengo, Noël C, Barricarte, Aurelio, Boeing, Heiner, Bonet, Catalina, Clavel-Chapelon, Françoise, Dartois, Laureen, Fagherazzi, Guy, Franks, Paul W, Huerta, José María, Kaaks, Rudolf, Key, Timothy J, Khaw, Kay Tee, Li, Kuanrong, Mühlenbruch, Kristin, Nilsson, Peter M, Overvad, Kim, Overvad, Thure F, Palli, Domenico, Panico, Salvatore, Quirós, J Ramón, Rolandsson, Olov, Roswall, Nina, Sacerdote, Carlotta, Sánchez, María-José, Slimani, Nadia, Tagliabue, Giovanna, Tjønneland, Anne, Tumino, Rosario, van der A, Daphne L, Forouhi, Nita G, Sharp, Stephen J, Langenberg, Claudia, Riboli, Elio, Wareham, Nicholas J
Publikováno v:
In The Lancet Diabetes & Endocrinology January 2014 2(1):19-29
Autor:
Vernooij, Lisette M, Klei, Wilton A, Moons, Karel GM, Takada, Toshihiko, Waes, Judith, Damen, Johanna AAG
Publikováno v:
Cochrane Database Syst Rev
BACKGROUND: The Revised Cardiac Risk Index (RCRI) is a widely acknowledged prognostic model to estimate preoperatively the probability of developing in‐hospital major adverse cardiac events (MACE) in patients undergoing noncardiac surgery. However,
Publikováno v:
In Journal of Clinical Epidemiology April 2021 132:142-145
Autor:
Puhan, Milo A, Garcia-Aymerich, Judith, Frey, Martin, ter Riet, Gerben, Antó, Josep M, Agustí, Alvar G, Gómez, Federico P, Rodríguez-Roisín, Roberto, Moons, Karel GM, Kessels, Alphons G, Held, Ulrike
Publikováno v:
In The Lancet 2009 374(9691):704-711
Autor:
Snell, Kym IE, Allotey, John, Smuk, Melanie, Hooper, Richard, Chan, Claire, Ahmed, Asif, Chappell, Lucy C, Von Dadelszen, Peter, Green, Marcus, Kenny, Louise, Khalil, Asma, Khan, Khalid S, Mol, Ben W, Myers, Jenny, Poston, Lucilla, Thilaganathan, Basky, Staff, Anne C, Smith, Gordon CS, Ganzevoort, Wessel, Laivuori, Hannele, Odibo, Anthony O, Arenas Ramírez, Javier, Kingdom, John, Daskalakis, George, Farrar, Diane, Baschat, Ahmet A, Seed, Paul T, Prefumo, Federico, da Silva Costa, Fabricio, Groen, Henk, Audibert, Francois, Masse, Jacques, Skråstad, Ragnhild B, Salvesen, Kjell Å, Haavaldsen, Camilla, Nagata, Chie, Rumbold, Alice R, Heinonen, Seppo, Askie, Lisa M, Smits, Luc JM, Vinter, Christina A, Magnus, Per, Eero, Kajantie, Villa, Pia M, Jenum, Anne K, Andersen, Louise B, Norman, Jane E, Ohkuchi, Akihide, Eskild, Anne, Bhattacharya, Sohinee, McAuliffe, Fionnuala M, Galindo, Alberto, Herraiz, Ignacio, Carbillon, Lionel, Klipstein-Grobusch, Kerstin, Yeo, Seon Ae, Browne, Joyce L, Moons, Karel GM, Riley, Richard D, Thangaratinam, Shakila, IPPIC Collaborative Network
BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclamps
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::f21799a4f02df39fe35816310e2ca9b5