Projects funded by the NCN
Application of machine-learning to clinical and imaging data for prediction of adverse events in patients undergoing transcatheter aortic valve implantation.
2021/41/B/NZ5/02630
Keywords:
Machine-learning aortic stenosis transcatheter aortic valve implantation prognosis risk score computed tomography
Descriptors:
- NZ5_5: Diagnostics in human diseases
- NZ7_16: Other related subjects
- ST6_7: Artificial intelligence, intelligent systems, multi-agent systems
Panel:
NZ5 - Human and animal noninfectious diseases: etiology, mechanisms, diagnosis and treatment of diseases, poisonings and injuries (without neurological diseases)
Host institution :
Narodowy Instytut Kardiologii Stefana kardynała Wyszyńskiego - Państwowy Instytut Badawczy
woj.
Principal investigator (from the host institution):
Number of co-investigators in the project: 3
Call: OPUS 21 - announced on 2021-03-15
Amount awarded: 767 063 PLN
Project start date (Y-m-d): 2022-01-17
Project end date (Y-m-d): 2026-01-16
Project duration:: 48 months (the same as in the proposal)
Project status: Pending project
Project description
Download the project description in a pdf file
Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.
Information in the final report
- Publication in academic press/journals (1)
- Machine learning for prediction of all-cause mortality after transcatheter aortic valve implantationAuthors:Jacek Kwiecinski, Maciej Dabrowski, Luis Nombela-Franco, Kajetan Grodecki, Konrad Pieszko, Zbigniew Chmielak, Anna Pylko, Breda Hennessey, Lukasz Kalinczuk, Gabriela Tirado-Conte, Bartosz Rymuza, Janusz Kochman, Maksymilian P Opolski, Zenon Huczek, Marc R Dweck, Damini Dey, Pilar Jimenez-Quevedo, Piotr Slomka, Adam WitkowskiAcademic press:European Heart Journal - Quality of Care and Clinical Outcomes (rok: 2023, tom: 9 (8), strony: 768–777), Wydawca: OxfordStatus:PublishedDOI:10.1093/ehjqcco/qcad002 - link to the publication