Machine learning for prediction of key haemodynamic parameters in pulmonary arterial hypertension.

Kramer T, Weis H, Kramer M, Baldus S, Rosenkranz S, Spinler S

DOI: 10.1093/ehjdh/ztaf074
Published: 2026 Jun
Container: European heart journal. Digital health
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1093/ehjdh/ztaf074,
  title = {Machine learning for prediction of key haemodynamic parameters in pulmonary arterial hypertension.},
  author = {Kramer T and Weis H and Kramer M and Baldus S and Rosenkranz S and Spinler S},
  year = {2026},
  journal = {European heart journal. Digital health},
  doi = {10.1093/ehjdh/ztaf074},
  url = {https://doi.org/10.1093/ehjdh/ztaf074}
}

RIS

TY  - JOUR
TI  - Machine learning for prediction of key haemodynamic parameters in pulmonary arterial hypertension.
AU  - Kramer T
AU  - Weis H
AU  - Kramer M
AU  - Baldus S
AU  - Rosenkranz S
AU  - Spinler S
PY  - 2026
JO  - European heart journal. Digital health
DO  - 10.1093/ehjdh/ztaf074
UR  - https://doi.org/10.1093/ehjdh/ztaf074
ER  -

APA

T, K., H, W., M, K., S, B., S, R., & S, S. (2026). Machine learning for prediction of key haemodynamic parameters in pulmonary arterial hypertension.. European heart journal. Digital health. https://doi.org/10.1093/ehjdh/ztaf074

Source records

pubmed · retrieved 2026-09-26T06:25:58.331Z