HOSPAITAL

Menu
DISSEMINATION & communication

Dissemination & Communication

Publications

Journal
  1. W. A. Sulaiman et al., “Leveraging Machine Learning and Rule Extraction for Enhanced Transparency in Emergency Department Length of Stay Prediction,” Frontiers in Digital Health, vol. 6, p. 1498939, 2024, doi: 10.3389/fdgth.2024.1498939.
  2. C. Stylianides et al., “AI Advances in ICU with an Emphasis on Sepsis Prediction: An Overview,” Machine Learning and Knowledge Extraction, vol. 7, no. 1, p. 6, 2025, doi: 10.3390/make7010006.
 
Conference
  1. A.Nicolaou et al., “An Overview of Explainable AI Studies in the Prediction of Sepsis Onset and Sepsis Mortality”. Studies in Health Technology and Informatics, 2024, pp808-812, doi:10.3233/shti240534.
  2. Aziz et al., “Emergency Department Length of Stay Classification Based on Ensemble Methods and Rule Extraction”. Studies in Health Technology and Informatics, 2024, pp. 1812-1816, doi: 10.3233/shti240783.
  3. C. -A. Alexandropoulou et al., “AI-Enabled Solutions, Explainability and Ethical Concerns for Predicting Sepsis in ICUs: A Systematic Review,” 2023 IEEE 19th International Conference on e-Science (e-Science), Limassol, Cyprus, 2023, pp. 1-9, doi: 10.1109/e-Science58273.2023.10254863.
  4. C. Stylianides et al., “AI-based solutions for predicting sepsis in ICUs,” 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, Malta, 2023, pp. 163-164, doi: 10.1109/IEEECONF58974.2023.10404309.
  5. W. A. Sulaiman et al., “Emergency Department Triage Hospitalization Prediction Based on Machine Learning and Rule Extraction,” 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, Malta, 2023, pp. 147-148, doi: 10.1109/IEEECONF58974.2023.10405176.
Workshop
  1. C. Stylianides et al., “AI-based solutions for predicting sepsis in ICUs”, 16th Cyprus Workshop on Signal Processing and Informatics (CWSPI), Limassol, Cyprus, July 2024.
  2. C.A. Alexandropoulou et al., “AI-enabled solutions for predicting sepsis in ICUs: a systematic review,” 15th Cyprus Workshop on Signal Processing and Informatics (CWSPI), Nicosia, Cyprus, July 2023.

Brand identity

The logo is our visual icon for the word, and it will be used on all materials. The logo has four versions:

One-page flyer

Hospital Transformation through AI flyer
The Project Hospital Transformation through Artificial Intelligence – HOSPAITAL, CODEVELOP-ICT-HEALTH/0322/0071 is funded by the European Union Recovery and Resilience Facility of the NextGenerationEU instrument, through the Research and Innovation Foundation.
Co-funded by
Scroll to Top