Big data analytics in adult congenital heart disease: why coding matters

Folkert W Asselbergs^{1

2

3}, Folkert J Meijboom¹

Affiliations

¹ Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, The Netherlands.
² Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK.
³ Health Data Research UK and Institute of Health Informatics, University College London, London, UK.

Comment

Folkert W Asselbergs et al. Eur Heart J. 2019.

. 2019 Apr 1;40(13):1078-1080.

doi: 10.1093/eurheartj/ehz089.

Folkert W Asselbergs^{1

2

3}, Folkert J Meijboom¹

¹ Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, The Netherlands.
² Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK.
³ Health Data Research UK and Institute of Health Informatics, University College London, London, UK.

No abstract available

Comment on

Machine learning algorithms estimating prognosis and guiding therapy in adult congenital heart disease: data from a single tertiary centre including 10 019 patients.
Diller GP, Kempny A, Babu-Narayan SV, Henrichs M, Brida M, Uebing A, Lammers AE, Baumgartner H, Li W, Wort SJ, Dimopoulos K, Gatzoulis MA. Diller GP, et al. Eur Heart J. 2019 Apr 1;40(13):1069-1077. doi: 10.1093/eurheartj/ehy915. Eur Heart J. 2019. PMID: 30689812 Free PMC article.