Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Schrempf Michael |
** = Publikationen gelistet in SCI/SSCI/Pubmed
2025
Originalarbeit (Zeitschrift)
** Berger, N; Kramer, D; Schrempf, M; Hofer, E; Pichler, A; Fandler-Höfler, S; Haidegger, M; Hatab, I; Heine, M; Jagiello, J; Koller, H; Lilek, S; Veeranki, S; Enzinger, C; Gattringer, T; Kneihsl, M
Predicting delirium in acute ischemic stroke: the PREDELIS score.
J Neurol. 2025; 272(6): 391
Doi: 10.1007/s00415-025-13073-5
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
** Lorenzer, L; Schrempf, M; Jauk, S; Kalabakov, S; Pierri, G; Suzuki, KMF; César, HV; Kramer, D; Mazzoncini, de, Azevedo-Marques, P; Rainer, P
Harmonization of Electronic Medical Records for Federated Learning: Addressing Challenges in International Healthcare Collaborations.
Stud Health Technol Inform. 2025; 324:141-147
Doi: 10.3233/SHTI250175
PubMed
FullText
FullText_MUG
2024
Originalarbeit (Zeitschrift)
** Kramer, D; Jauk, S; Veeranki, S; Schrempf, M; Traub, J; Kugel, E; Prisching, A; Domnanich, S; Leopold, M; Krisper, P; Sendlhofer, G
Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study.
Stud Health Technol Inform. 2024; 313: 156-157.
Doi: 10.3233/SHTI240029
PubMed
FullText
FullText_MUG
** Shimizu, GY; Schrempf, M; Romão, EA; Jauk, S; Kramer, D; Rainer, PP; Cardeal, da, Costa, JA; de, Azevedo-Marques, JM; Scarpelini, S; Suzuki, KMF; César, HV; de, Azevedo-Marques, PM
Machine learning-based risk prediction for major adverse cardiovascular events in a Brazilian hospital: Development, external validation, and interpretability.
PLoS One. 2024; 19(10):e0311719
Doi: 10.1371/journal.pone.0311719
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
2023
Originalarbeit (Zeitschrift)
** Polat, Erdeniz, S; Kramer, D; Schrempf, M; Rainer, PP; Felfernig, A; Tran, TNT; Burgstaller, T; Lubos, S
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events for ELGA-Authorized Clinics1.
Stud Health Technol Inform. 2023; 301: 20-25.
Doi: 10.3233/SHTI230006
PubMed
FullText
FullText_MUG