Streamlining management in thoracic trauma: radiomics- and AI-based assessment of patient risks
The study findings can be used to optimize the management of patients with a chest blunt injury as a specific case of monotrauma. The models we built may help physicians to stratify patients by risk of worsening and overcome the limitations of existing tools for risk assessment. High-quality AI models trained on radiomics data demonstrate superior performance.
Authors
- Yauhen Statsenko (ORCID: https://orcid.org/0000-0002-7713-3333)
- Nirmin A. Mansour
- Mai A. Fathi
- Taleb Mohamed Almansoori (ORCID: https://orcid.org/0000-0002-5723-4970)
- Ashraf F. Hefny
- Darya Smetanina (ORCID: https://orcid.org/0000-0002-4462-8823)
- Miloš Ljubisavljević (ORCID: https://orcid.org/0000-0002-5025-3562)
- Daria Morozova (ORCID: https://orcid.org/0000-0003-1443-4902)
- Karuna M. Das (ORCID: https://orcid.org/0000-0002-4703-5433)
- Aidar Kashapov
- Roman Voitetskii (ORCID: https://orcid.org/0000-0002-5477-981X)
- Mohammed Khogali (ORCID: https://orcid.org/0000-0001-8056-9114)
Institutions
- Ain Shams University (EG)
- United Arab Emirates University (AE)
- Abu Dhabi Health Services (AE)
Publication Details
- Journal
- Frontiers in Surgery
- Published
- 2024-10-24
- DOI
- https://doi.org/10.3389/fsurg.2024.1462692
- Citations
- 5
- Primary Topic
- Trauma Management and Diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 2.86