Enhancing the Understanding of Abdominal Trauma During the COVID-19 Pandemic Through Co-Occurrence Analysis and Machine Learning
Employing advanced co-occurrence analysis enhanced with machine learning, we uncovered complex relationships between clinical and demographic variables often overlooked by traditional methods. This innovative approach provided deeper insights into the collective impact of various factors on patient outcomes. Our findings demonstrate the healthcare system's rapid adaptations during the pandemic and offer critical insights for optimizing medical strategies and developing personalized interventions in global crises.
Authors
- D Rădulescu (ORCID: https://orcid.org/0009-0003-3990-6483)
- Răzvan Mercuţ (ORCID: https://orcid.org/0000-0001-8022-6306)
- Eleonora Daniela Ciupeanu-Călugăru
- Dan Calafeteanu
- I Georgescu
- Gheorghe-Jean Boldea
- Ana Maria Boldea
- Elena-Irina Caluianu
- P Rădulescu
- E Traşcă
- Georgiana-Andreea Marinescu
- E Georgescu
Institutions
- Clinical Emergency Hospital Bucharest (RO)
- University of Medicine and Pharmacy of Craiova (RO)
- University of Craiova (RO)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-10-31
- DOI
- https://doi.org/10.3390/diagnostics14212444
- Citations
- 2
- Primary Topic
- COVID-19 and healthcare impacts
- Type
- article
- Field-Weighted Citation Impact
- 0.57