Zobrazeno 1 - 10
of 1 502
pro vyhledávání: '"Moons, Karel G"'
Autor:
Whittle, Rebecca, Ensor, Joie, Archer, Lucinda, Collins, Gary S., Dhiman, Paula, Denniston, Alastair, Alderman, Joseph, Legha, Amardeep, van Smeden, Maarten, Moons, Karel G., Cazier, Jean-Baptiste, Riley, Richard D., Snell, Kym I. E.
When evaluating the performance of a model for individualised risk prediction, the sample size needs to be large enough to precisely estimate the performance measures of interest. Current sample size guidance is based on precisely estimating calibrat
Externí odkaz:
http://arxiv.org/abs/2406.19673
Autor:
Reinke, Annika, Tizabi, Minu D., Baumgartner, Michael, Eisenmann, Matthias, Heckmann-Nötzel, Doreen, Kavur, A. Emre, Rädsch, Tim, Sudre, Carole H., Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Benis, Arriel, Blaschko, Matthew, Buettner, Florian, Cardoso, M. Jorge, Cheplygina, Veronika, Chen, Jianxu, Christodoulou, Evangelia, Cimini, Beth A., Collins, Gary S., Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Glocker, Ben, Godau, Patrick, Haase, Robert, Hashimoto, Daniel A., Hoffman, Michael M., Huisman, Merel, Isensee, Fabian, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kenngott, Hannes, Kleesiek, Jens, Kofler, Florian, Kooi, Thijs, Kopp-Schneider, Annette, Kozubek, Michal, Kreshuk, Anna, Kurc, Tahsin, Landman, Bennett A., Litjens, Geert, Madani, Amin, Maier-Hein, Klaus, Martel, Anne L., Mattson, Peter, Meijering, Erik, Menze, Bjoern, Moons, Karel G. M., Müller, Henning, Nichyporuk, Brennan, Nickel, Felix, Petersen, Jens, Rafelski, Susanne M., Rajpoot, Nasir, Reyes, Mauricio, Riegler, Michael A., Rieke, Nicola, Saez-Rodriguez, Julio, Sánchez, Clara I., Shetty, Shravya, van Smeden, Maarten, Summers, Ronald M., Taha, Abdel A., Tiulpin, Aleksei, Tsaftaris, Sotirios A., Van Calster, Ben, Varoquaux, Gaël, Wiesenfarth, Manuel, Yaniv, Ziv R., Jäger, Paul F., Maier-Hein, Lena
Publikováno v:
Nature methods, 1-13 (2024)
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in im
Externí odkaz:
http://arxiv.org/abs/2302.01790
Autor:
Maier-Hein, Lena, Reinke, Annika, Godau, Patrick, Tizabi, Minu D., Buettner, Florian, Christodoulou, Evangelia, Glocker, Ben, Isensee, Fabian, Kleesiek, Jens, Kozubek, Michal, Reyes, Mauricio, Riegler, Michael A., Wiesenfarth, Manuel, Kavur, A. Emre, Sudre, Carole H., Baumgartner, Michael, Eisenmann, Matthias, Heckmann-Nötzel, Doreen, Rädsch, Tim, Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Benis, Arriel, Blaschko, Matthew, Cardoso, M. Jorge, Cheplygina, Veronika, Cimini, Beth A., Collins, Gary S., Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Haase, Robert, Hashimoto, Daniel A., Hoffman, Michael M., Huisman, Merel, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kenngott, Hannes, Kofler, Florian, Kopp-Schneider, Annette, Kreshuk, Anna, Kurc, Tahsin, Landman, Bennett A., Litjens, Geert, Madani, Amin, Maier-Hein, Klaus, Martel, Anne L., Mattson, Peter, Meijering, Erik, Menze, Bjoern, Moons, Karel G. M., Müller, Henning, Nichyporuk, Brennan, Nickel, Felix, Petersen, Jens, Rajpoot, Nasir, Rieke, Nicola, Saez-Rodriguez, Julio, Sánchez, Clara I., Shetty, Shravya, van Smeden, Maarten, Summers, Ronald M., Taha, Abdel A., Tiulpin, Aleksei, Tsaftaris, Sotirios A., Van Calster, Ben, Varoquaux, Gaël, Jäger, Paul F.
Publikováno v:
Nature methods, 1-18 (2024)
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus fa
Externí odkaz:
http://arxiv.org/abs/2206.01653
Autor:
Reinke, Annika, Tizabi, Minu D., Sudre, Carole H., Eisenmann, Matthias, Rädsch, Tim, Baumgartner, Michael, Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Bankhead, Peter, Benis, Arriel, Blaschko, Matthew, Buettner, Florian, Cardoso, M. Jorge, Chen, Jianxu, Cheplygina, Veronika, Christodoulou, Evangelia, Cimini, Beth, Collins, Gary S., Engelhardt, Sandy, Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Glocker, Ben, Godau, Patrick, Haase, Robert, Hamprecht, Fred, Hashimoto, Daniel A., Heckmann-Nötzel, Doreen, Hirsch, Peter, Hoffman, Michael M., Huisman, Merel, Isensee, Fabian, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kavur, A. Emre, Kenngott, Hannes, Kleesiek, Jens, Kleppe, Andreas, Kohler, Sven, Kofler, Florian, Kopp-Schneider, Annette, Kooi, Thijs, Kozubek, Michal, Kreshuk, Anna, Kurc, Tahsin, Landman, Bennett A., Litjens, Geert, Madani, Amin, Maier-Hein, Klaus, Martel, Anne L., Mattson, Peter, Meijering, Erik, Menze, Bjoern, Moher, David, Moons, Karel G. M., Müller, Henning, Nichyporuk, Brennan, Nickel, Felix, Noyan, M. Alican, Petersen, Jens, Polat, Gorkem, Rafelski, Susanne M., Rajpoot, Nasir, Reyes, Mauricio, Rieke, Nicola, Riegler, Michael, Rivaz, Hassan, Saez-Rodriguez, Julio, Sánchez, Clara I., Schroeter, Julien, Saha, Anindo, Selver, M. Alper, Sharan, Lalith, Shetty, Shravya, van Smeden, Maarten, Stieltjes, Bram, Summers, Ronald M., Taha, Abdel A., Tiulpin, Aleksei, Tsaftaris, Sotirios A., Van Calster, Ben, Varoquaux, Gaël, Wiesenfarth, Manuel, Yaniv, Ziv R., Jäger, Paul, Maier-Hein, Lena
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performan
Externí odkaz:
http://arxiv.org/abs/2104.05642
Autor:
Leeuwenberg, Artuur M., van Smeden, Maarten, Langendijk, Johannes A., van der Schaaf, Arjen, Mauer, Murielle E., Moons, Karel G. M., Reitsma, Johannes B., Schuit, Ewoud
Clinical prediction models are developed widely across medical disciplines. When predictors in such models are highly collinear, unexpected or spurious predictor-outcome associations may occur, thereby potentially reducing face-validity and explainab
Externí odkaz:
http://arxiv.org/abs/2101.01603
Autor:
Kappen, Teus H., Noordegraaf, Mirko, van Klei, Wilton A., Moons, Karel G. M., Kalkman, Cor J.
The aim of a clinical decision support tool is to reduce the complexity of clinical decisions. However, when decision support tools are poorly implemented they may actually confuse physicians and complicate clinical care. This paper argues that infor
Externí odkaz:
http://arxiv.org/abs/2003.00921
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