Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol

Lotte Rijken; Sabrina Zwetsloot; Stefan Smorenburg; Jelmer Wolterink; Ivana Isgum; Henk Marquering; Jan van Duivenvoorde; Corrette Ploem; Roosmarie Jessen; Fabio Catarinella; Regent Lee; Katarzyna Bera; Jenny Buisan; Ping Zhang; Marina Dias-Neto; Juliette Raffort; Fabian Lareyre; Catelijne Muller; Igor Koncar; Ivan Tomic; Maja Zivkovic; Tamara Djuric; Aleksandra Stankovic; Maarit Venermo; Riikka Tulamo; Christian-Alexander Behrendt; Noeska Smit; Marlies Schijven; Bert-Jan van den Born; Ronak Delewi; Vincent Jongkind; Venkat Ayyalasomayajula; Kak Khee Yeung

doi:10.1177/15266028251313963

Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol

Lotte Rijken, Sabrina Zwetsloot, Stefan Smorenburg, Jelmer Wolterink, Ivana Isgum, Henk Marquering, Jan van Duivenvoorde, Corrette Ploem, Roosmarie Jessen, Fabio Catarinella, Regent Lee, Katarzyna Bera, Jenny Buisan, Ping Zhang, Marina Dias-Neto, Juliette Raffort, Fabian Lareyre, Catelijne Muller, Igor Koncar, Ivan TomicMaja Zivkovic, Tamara Djuric, Aleksandra Stankovic, Maarit Venermo, Riikka Tulamo, Christian-Alexander Behrendt, Noeska Smit, Marlies Schijven, Bert-Jan van den Born, Ronak Delewi, Vincent Jongkind, Venkat Ayyalasomayajula, Kak Khee Yeung

Forskningsoutput: Tidskriftsbidrag › Artikel › Vetenskaplig › Peer review

Originalspråk	engelska
Tidskrift	Journal of Endovascular Therapy
Antal sidor	9
ISSN	1526-6028
DOI	https://doi.org/10.1177/15266028251313963
Status	!!E-pub ahead of print - feb. 2025
MoE-publikationstyp	A1 Tidskriftsartikel-refererad

Åtkomst av dokument

10.1177/15266028251313963

Citera det här

Rijken, L., Zwetsloot, S., Smorenburg, S., Wolterink, J., Isgum, I., Marquering, H., van Duivenvoorde, J., Ploem, C., Jessen, R., Catarinella, F., Lee, R., Bera, K., Buisan, J., Zhang, P., Dias-Neto, M., Raffort, J., Lareyre, F., Muller, C., Koncar, I., ... Khee Yeung, K. (2025). Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol. Journal of Endovascular Therapy. Avancerad onlinepublikation. https://doi.org/10.1177/15266028251313963

@article{13d3b3ac9079419dac113002bb1804c5,

title = "Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol",

keywords = "Abdominal aortic aneurysm, Artificial intelligence, Cardiovascular risk, Disease progression, Multimodal data, Peripheral arterial disease",

author = "Lotte Rijken and Sabrina Zwetsloot and Stefan Smorenburg and Jelmer Wolterink and Ivana Isgum and Henk Marquering and {van Duivenvoorde}, Jan and Corrette Ploem and Roosmarie Jessen and Fabio Catarinella and Regent Lee and Katarzyna Bera and Jenny Buisan and Ping Zhang and Marina Dias-Neto and Juliette Raffort and Fabian Lareyre and Catelijne Muller and Igor Koncar and Ivan Tomic and Maja Zivkovic and Tamara Djuric and Aleksandra Stankovic and Maarit Venermo and Riikka Tulamo and Christian-Alexander Behrendt and Noeska Smit and Marlies Schijven and {van den Born}, Bert-Jan and Ronak Delewi and Vincent Jongkind and Venkat Ayyalasomayajula and {Khee Yeung}, Kak",

year = "2025",

month = feb,

doi = "10.1177/15266028251313963",

language = "English",

journal = "Journal of Endovascular Therapy",

issn = "1526-6028",

publisher = "SAGE Publications Inc.",

}

Rijken, L, Zwetsloot, S, Smorenburg, S, Wolterink, J, Isgum, I, Marquering, H, van Duivenvoorde, J, Ploem, C, Jessen, R, Catarinella, F, Lee, R, Bera, K, Buisan, J, Zhang, P, Dias-Neto, M, Raffort, J, Lareyre, F, Muller, C, Koncar, I, Tomic, I, Zivkovic, M, Djuric, T, Stankovic, A, Venermo, M , Tulamo, R, Behrendt, C-A, Smit, N, Schijven, M, van den Born, B-J, Delewi, R, Jongkind, V, Ayyalasomayajula, V & Khee Yeung, K 2025, 'Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol', Journal of Endovascular Therapy. https://doi.org/10.1177/15266028251313963

TY - JOUR

T1 - Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression

T2 - the VASCUL-AID-RETRO Study Protocol

AU - Rijken, Lotte

AU - Zwetsloot, Sabrina

AU - Smorenburg, Stefan

AU - Wolterink, Jelmer

AU - Isgum, Ivana

AU - Marquering, Henk

AU - van Duivenvoorde, Jan

AU - Ploem, Corrette

AU - Jessen, Roosmarie

AU - Catarinella, Fabio

AU - Lee, Regent

AU - Bera, Katarzyna

AU - Buisan, Jenny

AU - Zhang, Ping

AU - Dias-Neto, Marina

AU - Raffort, Juliette

AU - Lareyre, Fabian

AU - Muller, Catelijne

AU - Koncar, Igor

AU - Tomic, Ivan

AU - Zivkovic, Maja

AU - Djuric, Tamara

AU - Stankovic, Aleksandra

AU - Venermo, Maarit

AU - Tulamo, Riikka

AU - Behrendt, Christian-Alexander

AU - Smit, Noeska

AU - Schijven, Marlies

AU - van den Born, Bert-Jan

AU - Delewi, Ronak

AU - Jongkind, Vincent

AU - Ayyalasomayajula, Venkat

AU - Khee Yeung, Kak

PY - 2025/2

Y1 - 2025/2

KW - Abdominal aortic aneurysm

KW - Artificial intelligence

KW - Cardiovascular risk

KW - Disease progression

KW - Multimodal data

KW - Peripheral arterial disease

U2 - 10.1177/15266028251313963

DO - 10.1177/15266028251313963

M3 - Article

C2 - 39921236

SN - 1526-6028

JO - Journal of Endovascular Therapy

JF - Journal of Endovascular Therapy

ER -