Prokosch, Hans-Ulrich

eHealth Trends in Europe 2005-2007: A Population-Based Survey

Kummervold, P. E., Chronaki, C. E., Lausen, B., Prokosch, H.-U., Rasmussen, J., Santana, S., Staniszewski, A., & Wangberg, S. C. (2008) · Journal of Medical Internet Research

Health Literacy and Information AccessibilityHealth, Technology, Consumer Behavior

Cited by 449

KETOS: Clinical decision support and machine learning as a service – A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services

Gruendner, J., Schwachhofer, T., Sippl, P., Wolf, N., Erpenbeck, M., Gulden, C., Kapsner, L. A., Zierk, J., Mate, S., Stürzl, M., et al. (2019) · PLOS ONE

Electronic Health Records SystemsMachine Learning in Healthcare

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Results from the German Chronic Kidney Disease (GCKD) study support association of relative telomere length with mortality in a large cohort of patients with moderate chronic kidney disease

Fazzini, F., Lamina, C., Raschenberger, J., Schultheiss, U. T., Kotsis, F., Schönherr, S., Weissensteiner, H., Forer, L., Steinbrenner, I., Meiselbach, H., et al. (2020) · Kidney International

Telomeres, Telomerase, and SenescenceChronic Kidney Disease and Diabetes

Cited by 38

Attitudes and Acceptance Towards Artificial Intelligence in Medical Care

Holzner, D., Apfelbacher, T., Rödle, W., Schüttler, C., Prokosch, H.-U., Mikolajczyk, R., Negash, S., Kartschmit, N., Manuilova, I., Buch, C., et al. (2022) · Studies in Health Technology and Informatics

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

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