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Stevens, Marthe, Beaulieu, Anne
Veröffentlicht in: Stevens , M & Beaulieu , A 2024 , ' A careful approach to artificial intelligence : the struggles with epistemic responsibility of healthcare professionals ' , Information Communication and Society , vol. 27 , no. 4 , pp. 719-734 . https://doi.org/10.1080/1369118X.2023.2289971;
2024
Veröffentlicht in: Stevens , M & Beaulieu , A 2024 , ' A careful approach to artificial intelligence : the struggles with epistemic responsibility of healthcare professionals ' , Information Communication and Society , vol. 27 , no. 4 , pp. 719-734 . https://doi.org/10.1080/1369118X.2023.2289971;
2024
13
14
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16
Shi, X., Nikolic, G., Van Pottelbergh, G., Van den Akker, M., Vos, R., De Moor, B.
Veröffentlicht in: Shi , X , Nikolic , G , Van Pottelbergh , G , Van den Akker , M , Vos , R & De Moor , B 2021 , ' Development of Multimorbidity Over Time: An Analysis of Belgium Primary Care Data Using Markov Chains and Weighted Association Rule Mining ' , Journals of Gerontology Series A-Biological Sciences and Medical Sciences , vol. 76 , no. 7 , pp. 1234-1241 . https://doi.org/10.1093/gerona/glaa278;
2021
Veröffentlicht in: Shi , X , Nikolic , G , Van Pottelbergh , G , Van den Akker , M , Vos , R & De Moor , B 2021 , ' Development of Multimorbidity Over Time: An Analysis of Belgium Primary Care Data Using Markov Chains and Weighted Association Rule Mining ' , Journals of Gerontology Series A-Biological Sciences and Medical Sciences , vol. 76 , no. 7 , pp. 1234-1241 . https://doi.org/10.1093/gerona/glaa278;
2021
17
Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands:CVON-AI consortium
Benjamins, J W, van Leeuwen, K, Hofstra, L, Rienstra, M, Appelman, Y, Nijhof, W, Verlaat, B, Everts, I, den Ruijter, H M, Isgum, I, Leiner, T, Vliegenthart, R, Asselbergs, F W, Juarez-Orozco, L E, van der Harst, P
Veröffentlicht in: Benjamins , J W , van Leeuwen , K , Hofstra , L , Rienstra , M , Appelman , Y , Nijhof , W , Verlaat , B , Everts , I , den Ruijter , H M , Isgum , I , Leiner , T , Vliegenthart , R , Asselbergs , F W , Juarez-Orozco , L E & van der Harst , P 2019 , ' Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands : CVON-AI consortium ' , Netherlands Heart Hournal , vol. 27 , no. 9 , pp. 414-425 . https://doi.org/10.1007/s12471-019-1281-y;
2019
Veröffentlicht in: Benjamins , J W , van Leeuwen , K , Hofstra , L , Rienstra , M , Appelman , Y , Nijhof , W , Verlaat , B , Everts , I , den Ruijter , H M , Isgum , I , Leiner , T , Vliegenthart , R , Asselbergs , F W , Juarez-Orozco , L E & van der Harst , P 2019 , ' Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands : CVON-AI consortium ' , Netherlands Heart Hournal , vol. 27 , no. 9 , pp. 414-425 . https://doi.org/10.1007/s12471-019-1281-y;
2019
18
19
Fleuren, Lucas M., Tonutti, Michele, de Bruin, Daan P., Lalisang, Robbert C. A., Dam, Tariq A., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Vonk, Sebastiaan J. J., Fornasa, Mattia, Machado, Tomas, van der Meer, Nardo J. M., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco, Kamps, Marlijn J. A., Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert, Cornet, Alexander D., van den Tempel, Walter, Boelens, Age D., Koetsier, Peter, Lens, Judith, Achterberg, Sefanja, Faber, Harald J., Karakus, A., Beukema, Menno, Entjes, Robert, de Jong, Paul, Houwert, Taco, Hovenkamp, Hidde, Noorduijn Londono, Roberto, Quintarelli, Davide, Scholtemeijer, Martijn G., de Beer, Aletta A., van Osch, Frits, Aries, Marcel
Veröffentlicht in: Fleuren , L M , Tonutti , M , de Bruin , D P , Lalisang , R C A , Dam , T A , Gommers , D , Cremer , O L , Bosman , R J , Vonk , S J J , Fornasa , M , Machado , T , van der Meer , N J M , 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 , Oostdijk , E , Reidinga , A C , Festen-Spanjer , B , Brunnekreef , G , Cornet , A D , van den Tempel , W , Boelens , A D , Koetsier , P , Lens , J , Achterberg , S , Faber , H J , Karakus , A , Beukema , M , Entjes , R , de Jong , P , Houwert , T , Hovenkamp , H , Noorduijn Londono , R , Quintarelli , D , Scholtemeijer , M G , de Beer , A A , Dutch ICU Data Sharing Against Covid-19 Collaborators , van Osch , F & Aries , M 2021 , ' Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients : a multicenter machine learning study with highly granular data from the Dutch Data Warehouse ' , Intensive Care Medicine Experimental , vol. 9 , no. 1 , 32 . https://doi.org/10.1186/s40635-021-00397-5;
2021
Veröffentlicht in: Fleuren , L M , Tonutti , M , de Bruin , D P , Lalisang , R C A , Dam , T A , Gommers , D , Cremer , O L , Bosman , R J , Vonk , S J J , Fornasa , M , Machado , T , van der Meer , N J M , 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 , Oostdijk , E , Reidinga , A C , Festen-Spanjer , B , Brunnekreef , G , Cornet , A D , van den Tempel , W , Boelens , A D , Koetsier , P , Lens , J , Achterberg , S , Faber , H J , Karakus , A , Beukema , M , Entjes , R , de Jong , P , Houwert , T , Hovenkamp , H , Noorduijn Londono , R , Quintarelli , D , Scholtemeijer , M G , de Beer , A A , Dutch ICU Data Sharing Against Covid-19 Collaborators , van Osch , F & Aries , M 2021 , ' Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients : a multicenter machine learning study with highly granular data from the Dutch Data Warehouse ' , Intensive Care Medicine Experimental , vol. 9 , no. 1 , 32 . https://doi.org/10.1186/s40635-021-00397-5;
2021
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