Marx, Gernot

Swarm Learning for decentralized and confidential clinical machine learning

Warnat-Herresthal, S., Schultze, H., Shastry, K. L., Manamohan, S., Mukherjee, S., Garg, V., Sarveswara, R., Händler, K., Pickkers, P., Aziz, N. A., et al. (2021) · Nature

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

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Chemokine (C‐C motif) receptor 2–positive monocytes aggravate the early phase of acetaminophen‐induced acute liver injury

Mossanen, J. C., Krenkel, O., Ergen, C., Govaere, O., Liepelt, A., Puengel, T., Heymann, F., Kalthoff, S., Lefebvre, E., Eulberg, D., et al. (2016) · Hepatology

Drug-Induced Hepatotoxicity and ProtectionLiver physiology and pathology

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Effect of Sodium Selenite Administration and Procalcitonin-Guided Therapy on Mortality in Patients With Severe Sepsis or Septic Shock: A Randomized Clinical Trial

Bloos, F., Trips, E., Nierhaus, A., Briegel, J., Heyland, D. K., Jaschinski, U., Moerer, O., Weyland, A., Marx, G., Gründling, M., et al. (2016) · JAMA Internal Medicine

Sepsis Diagnosis and TreatmentVitamin C and Antioxidants Research

Cited by 268

Role of nutrition support in adult cardiac surgery: a consensus statement from an International Multidisciplinary Expert Group on Nutrition in Cardiac Surgery

Stoppe, C., Goetzenich, A., Whitman, G., Ohkuma, R., Brown, T., Hatzakorzian, R., Kristof, A., Meybohm, P., Mechanick, J., Evans, A., et al. (2017) · Critical Care

Clinical Nutrition and GastroenterologyHemodynamic Monitoring and Therapy

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Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey

Maassen, O., Fritsch, S., Palm, J., Deffge, S., Kunze, J., Marx, G., Riedel, M., Schuppert, A., & Bickenbach, J. (2021) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 125

Persistent low serum zinc is associated with recurrent sepsis in critically ill patients - A pilot study

Hoeger, J., Simon, T.-P., Beeker, T., Marx, G., Haase, H., & Schuerholz, T. (2017) · PLOS ONE

Sepsis Diagnosis and TreatmentTrace Elements in Health

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Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

Magunia, H., Lederer, S., Verbuecheln, R., Gilot, B. J., Koeppen, M., Haeberle, H. A., Mirakaj, V., Hofmann, P., Marx, G., Bickenbach, J., et al. (2021) · Critical Care

COVID-19 Clinical Research StudiesMachine Learning in Healthcare

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Predicting abnormalities in laboratory values of patients in the intensive care unit using different deep learning models: comparative study

Ayad, A., Hallawa, A., Peine, A., Martin, L., Fazlic, L. B., Dartmann, G., Marx, G., & Schmeink, A. (2022) · JMIR Medical Informatics

Machine Learning in HealthcareAnomaly Detection Techniques and Applications

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Application of convex hull analysis for the evaluation of data heterogeneity between patient populations of different origin and implications of hospital bias in downstream machine-learning-based data processing: A comparison of 4 critical-care patient datasets

Sharafutdinov, K., Bhat, J. S., Fritsch, S. J., Nikulina, K., E. Samadi, M., Polzin, R., Mayer, H., Marx, G., Bickenbach, J., & Schuppert, A. (2022) · Frontiers in Big Data

Machine Learning in HealthcareArtificial Intelligence in Healthcare

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Haemoglobin value and red blood cell transfusions in prolonged weaning from mechanical ventilation: a retrospective observational study

Fritsch, S. J., Dreher, M., Simon, T.-P., Marx, G., & Bickenbach, J. (2022) · BMJ Open Respiratory Research

Respiratory Support and MechanismsBlood transfusion and management

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