Interactive algorithms for teaching and learning acute medicine in the network of medical faculties MEFANET.
Daniel SchwarzPetr ŠtouračMartin KomendaHana HarazimMartina KosinováJakub GregorRichard HůlekOlga SmékalováIvo KřikavaRoman ŠtoudekLadislav DušekPublished in: Journal of medical Internet research (2013)
The peer-reviewed algorithms were used for conducting problem-based learning sessions in general medicine (first aid, anesthesiology and pain management, emergency medicine) and in nursing (emergency medicine for midwives, obstetric analgesia, and anesthesia for midwifes). The feedback from the survey suggests that the students found the interactive algorithms as effective learning tools, facilitating enhanced knowledge in the field of acute medicine. The interactive algorithms, as a software platform, are open to academic use worldwide. The existing algorithms, in the form of simulation-based learning objects, can be incorporated into any educational website (subject to the approval of the authors).
Keyphrases
- machine learning
- emergency medicine
- pain management
- deep learning
- healthcare
- liver failure
- respiratory failure
- chronic pain
- pregnant women
- mental health
- high throughput
- minimally invasive
- quality improvement
- medical students
- intensive care unit
- hepatitis b virus
- single cell
- acute respiratory distress syndrome
- high school
- drug administration