Challenges in developing and validating machine learning models for TAVI mortality risk prediction: reply-Reference-Cited by-同舟云学术

Challenges in developing and validating machine learning models for TAVI mortality risk prediction: reply

Published:2023-11-08 Issue:1 Volume:5 Page:3-5
ISSN:2634-3916
Container-title:European Heart Journal - Digital Health
language:en
Short-container-title:

Author:

Leha Andreas¹²,Huber Cynthia¹,Friede Tim¹²^ORCID,Bauer Timm³,Beckmann Andreas⁴⁵,Bekeredjian Raffi⁶,Bleiziffer Sabine⁷^ORCID,Herrmann Eva⁸⁹^ORCID,Möllmann Helge¹⁰,Walther Thomas¹¹^ORCID,Beyersdorf Friedhelm¹²¹³^ORCID,Hamm Christian¹⁴¹⁵,Künzi Arnaud¹⁶,Windecker Stephan¹⁷^ORCID,Stortecky Stefan¹⁷,Kutschka Ingo¹⁸^ORCID,Hasenfuß Gerd²¹⁹,Ensminger Stephan²⁰²¹^ORCID,Frerker Christian²¹²²,Seidler Tim²¹⁹^ORCID

Affiliation:

1. Department of Medical Statistics, University Medical Center Göttingen , Humboldtallee 32, 37073 Göttingen, Germany

2. DZHK (German Center for Cardiovascular Research) , Partner Site Göttingen, Robert-Koch str. 40, 37075 Göttingen, Germany

3. Department of Cardiology, Sana Klinikum Offenbach , Starkenburgring 66, 63069 Offenbach am Main, Germany

4. German Society for Thoracic and Cardiovascular Surgery, Langenbeck-Virchow-Haus , Luisenstraße 58/59, 10117 Berlin, Germany

5. Department for Cardiac and Pediatric Cardiac Surgery, Heart Center Duisburg, EVKLN , Gerrickstr. 21, 47137 Duisburg , Germany

6. Department of Cardiology, Robert-Bosch-Krankenhaus , Auerbachstraße 110, 70376 Stuttgart, Germany

7. Clinic for Thoracic and Cardiovascular Surgery, Heart and Diabetes Center Northrhine-Westphalia , Georgstr 11, 32545 Bad Oeynhausen, Germany

8. Goethe University Frankfurt, Department of Medicine, Institute of Biostatistics and Mathematical Modelling , Theodor-Stern-Kai 7, 60590 Frankfurt Main, Germany

9. DZHK (German Centre for Cardiovascular Research) , Partner Site Rhine/Main, Theodor-Stern-Kai 7, 60590 Frankfurt Main, Germany

10. Department of Cardiology, St.-Johannes-Hospital Dortmund , Johannesstrasse 9-17, 44137 Dortmund, Germany

11. Department of Cardiothoracic Surgery, University Hospital Frankfurt , Theodor-Stern-Kai 7, 60590 Frankfurt, Germany

12. Medical Faculty of the Albert-Ludwigs-University Freiburg, University Hospital Freiburg , Hugstetterstr. 55, 79106 Freiburg, Germany

13. Department of Cardiovascular Surgery, Heart Centre Freiburg University , Freiburg , Germany

14. Department of Cardiology and Angiology, University Hospital Gießen , Klinikstr. 33, 35392 Gießen, Germany

15. Department of Cardiology, Kerckhoff Heart and Thorax Center , Benekestraße 2-8, D-61231 Bad Nauheim , Germany

16. CTU Bern, University of Bern , Mittelstrasse 43, 3012 Bern, Switzerland

17. Department of Cardiology, Inselspital, Bern University Hospital, University of Bern , 3010 Bern, Switzerland

18. Clinic for Cardiothoracic and Vascular Surgery/Heart Center, University Medical Center Göttingen , Robert-Koch Str. 40, 37075 Göttingen, Germany

19. Clinic for Cardiology and Pulmonology, Heart Center, University Medical Center Göttingen , Robert-Koch Str. 40, 37075 Göttingen, Germany

20. Department of Cardiac and Thoracic Vascular Surgery, University Heart Center Lübeck , Ratzeburger Allee 160, 23538 Lübeck, Germany

21. DZHK (German Centre for Cardiovascular Research) , partner site Hamburg/Kiel/Lübeck, Lübeck , Germany

22. Department of Cardiology, University Heart Center Lübeck , Ratzeburger Allee 160, 23538 Lübeck, Germany

Publisher

Oxford University Press (OUP)

Subject

Energy Engineering and Power Technology,Fuel Technology

Link

https://academic.oup.com/ehjdh/advance-article-pdf/doi/10.1093/ehjdh/ztad065/53811195/ztad065.pdf

Reference12 articles.

1. Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores;Leha;Eur Heart J Digit Health,2023

2. Challenges in developing and validating machine learning models for transcatheter aortic valve implantation mortality risk prediction;Kazemian;Eur Heart J Digit Health,2024

3. Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations;Friedrich;Eur Heart J Digit Health,2021

4. A plea for neutral comparison studies in computational sciences;Boulesteix;PLos One,2013

5. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges;Goldstein;Eur Heart J,2017