Personal profile
Research interests
Continuous non-invasive monitoring of volatile metabolites in exhaled breath as markers of plasma glucose levels
Specialisation
Medical Informatics, Intensive Care
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Dive into the research topics where Jan Hendrik Leopold is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Requirements for Manual Knowledge Acquisition Tools: Systematic Literature Review and Expert Panel Consensus
van Brummelen, N., Leopold, J. H. & Medlock, S., 1 Dec 2025, In: Journal of medical systems. 49, 1, 164.Research output: Contribution to journal › Article › Academic › peer-review
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Adverse drug events caused by three high-risk drug-drug interactions in patients admitted to intensive care units: A multicentre retrospective observational study
Klopotowska, J. E., Leopold, J.-H., Bakker, T., Yasrebi-de Kom, I., Engelaer, F. M., de Jonge, E., Haspels-Hogervorst, E. K., van den Bergh, W. M., Renes, M. H., Jong, B. T. D., Kieft, H., Wieringa, A., Hendriks, S., Lau, C., van Bree, S. H. W., Lammers, H. J. W., Wierenga, P. C., Bosman, R. J., de Jong, V. M. & Slijkhuis, M. & 11 others, , Jan 2024, In: British journal of clinical pharmacology. 90, 1, p. 164-175 12 p.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile45 Downloads (Pure) -
Adverse drug event detection using natural language processing: A scoping review of supervised learning methods
Murphy, R. M., Klopotowska, J. E., de Keizer, N. F., Jager, K. J., Leopold, J. H., Dongelmans, D. A., Abu-Hanna, A. & Schut, M. C., Jan 2023, In: PLoS ONE. 18, 1 January, p. e0279842 e0279842.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile42 Downloads (Pure) -
Microbial Volatiles as Diagnostic Biomarkers of Bacterial Lung Infection in Mechanically Ventilated Patients
BreathDx Consortium, 15 Mar 2023, In: Clinical infectious diseases. 76, 6, p. 1059-1066 8 p.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile33 Downloads (Pure) -
Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal
Vagliano, I., Chesnaye, N. C., Leopold, J. H., Jager, K. J., Abu-Hanna, A. & Schut, M. C., 1 Dec 2022, In: Clinical kidney journal. 15, 12, p. 2266-2280 sfac181.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile24 Downloads (Pure)