This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1326) Clinical Information and Decision Making (1615)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20407, first published .
The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation

The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation

The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation

Authors of this article:

Maria Beatriz Walter Costa1, 2 Author Orcid Image ;   Mark Wernsdorfer1, 2 Author Orcid Image ;   Alexander Kehrer3 Author Orcid Image ;   Markus Voigt4 Author Orcid Image ;   Carina Cundius4 Author Orcid Image ;   Martin Federbusch1 Author Orcid Image ;   Felix Eckelt1 Author Orcid Image ;   Johannes Remmler1 Author Orcid Image ;   Maria Schmidt1, 2 Author Orcid Image ;   Sarah Pehnke1 Author Orcid Image ;   Christiane Gärtner1, 2 Author Orcid Image ;   Markus Wehner5 Author Orcid Image ;   Berend Isermann1 Author Orcid Image ;   Heike Richter5 Author Orcid Image ;   Jörg Telle3 Author Orcid Image ;   Thorsten Kaiser1 Author Orcid Image
Article Authors Cited by (9) Tweetations (1) Metrics

Journals

  1. Sicker T, Federbusch M, Eckelt F, Isermann B, Fenske W, Fries C, Schmidt M, Kaiser T. Challenge in hyponatremic patients – the potential of a laboratory-based decision support system for hyponatremia to improve patient’s safety. Clinical Chemistry and Laboratory Medicine (CCLM) 2023;61(6):1025 View
  2. Boss K, Roller R, Woywodt A, Kribben A, Budde K, Becker S. Künstliche Intelligenz in der Nephrologie. Die Nephrologie 2022;17(6):399 View
  3. Kotzerke D, Costa M, Voigt J, Kleinhempel A, Schmidt M, Söhnlein T, Kaiser T, Henschler R. Novelle QLL 2020 – welche Auswirkungen haben die neu empfohlenen Hämoglobin-Transfusionstrigger auf die klinische Versorgung?. Transfusionsmedizin 2022;12(01):26 View
  4. Heuft L, Voigt J, Selig L, Stumvoll M, Schlögl H, Kaiser T. Refeeding syndrome—diagnostic challenges and the potential of clinical decision support systems. Deutsches Ärzteblatt international 2023 View
  5. Heuft L, Voigt J, Selig L, Schmidt M, Eckelt F, Steinbach D, Federbusch M, Stumvoll M, Schlögl H, Isermann B, Kaiser T. Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study. Nutrients 2023;15(17):3712 View
  6. Schmidt M, Steinbach D, Federbusch M, Tönjes A, Isermann B, Kaiser T, Eckelt F. Evidence-based cutoffs for total and adjusted calcium: a major factor in detecting severe hypo- and hypercalcemia. Clinical Chemistry and Laboratory Medicine (CCLM) 2024;62(7):1367 View
  7. Steinbach D, Ahrens P, Schmidt M, Federbusch M, Heuft L, Lübbert C, Nauck M, Gründling M, Isermann B, Gibb S, Kaiser T. Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission. Clinical Chemistry 2024;70(3):506 View
  8. Romero A, Gomez-Lumbreras A, Villa-Zapata L, Tan M, Horn J, Malone D. Evaluation of an electronic health record Drug Interaction Customization Editor (DICE). American Journal of Health-System Pharmacy 2024;81(22):1142 View

Books/Policy Documents

  1. Matricardi P, Bousquet J. Digital Allergology. View