| MIMIC-IV as a clinical data schema N Giesa, P Heeren, S Klopfenstein, A Flint, L Agha-Mir-Salim, A Poncette, ... Challenges of Trustable AI and Added-Value on Health, 559-560, 2022 | 16 | 2022 |
| A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability study E Williams, M Kienast, E Medawar, J Reinelt, A Merola, SAI Klopfenstein, ... JMIR Medical Informatics 11, e43847, 2023 | 8 | 2023 |
| The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study ZC Sinno, D Shay, J Kruppa, SAI Klopfenstein, N Giesa, AR Flint, ... Scientific Reports 12 (1), 21801, 2022 | 4 | 2022 |
| How to Annotate Patient Monitoring Alarms in Intensive Care Medicine for Machine Learning SAI Klopfenstein, AR Flint, P Heeren, M Prendke, A Chaoui, T Ocker, ... | 3 | 2023 |
| Utilizing Intensive Care Alarms for Machine Learning AR Flint, SAI Klopfenstein, P Heeren, F Balzer, AS Poncette Challenges of Trustable AI and Added-Value on Health, 273-274, 2022 | 1 | 2022 |
| Alarm Management in Intensive Care: Qualitative Triangulation Study L Mosch, M Sümer, AR Flint, M Feufel, F Balzer, F Mörike, AS Poncette JMIR Human Factors 11, e55571, 2024 | | 2024 |
| ARTEMIS: An alarm threshold and policy mining system for the intensive care unit J Chromik, AR Flint, B Arnrich International Journal of Medical Informatics 184, 105349, 2024 | | 2024 |
| FHIR-DHP: A Standardized Clinical Data Harmonisation Pipeline for scalable AI application deployment E Williams, M Kienast, E Medawar, J Reinelt, A Merola, ... medRxiv, 2022.11. 07.22281564, 2022 | | 2022 |
