Artificial intelligence in pulmonary hypertension: a systematic review
ML and DL models show promise for PH and PAH diagnosis and prognosis, but limitations in subclass differentiation, methodological transparency, and validation must be addressed in future research.
Authors
- Christian Hagist (ORCID: https://orcid.org/0000-0002-6322-3178)
- Stefan Spinler (ORCID: https://orcid.org/0000-0003-2669-4728)
- Tilmann Kramer (ORCID: https://orcid.org/0000-0003-0265-7607)
- Mira Krämer (ORCID: https://orcid.org/0009-0001-3464-0802)
Institutions
- University of Cologne (DE)
- University Hospital Ulm (DE)
- WHU – Otto Beisheim School of Management (DE)
Publication Details
- Journal
- European journal of medical research
- Published
- 2025-12-08
- DOI
- https://doi.org/10.1186/s40001-025-03557-5
- Citations
- 3
- Primary Topic
- Pulmonary Hypertension Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 4.56