Hybrid Artificial Intelligence Solution Combining Convolutional Neural Network and Analytical Approach Showed Higher Accuracy in A-lines Detection on Lung Ultrasound in Thoracic Surgery Patients Compared with Radiology Resident.
Artificial intelligence showed high accuracy in A-line detection in thoracic surgery patients and was more accurate compared to a resident. Artificial intelligence could play important role in lung ultrasound artifact detection in thoracic surgery patients and in residents' education.
Authors
- Anton Dzian (ORCID: https://orcid.org/0000-0002-4883-3605)
- Zuzana Trabalková
- Beata Sániová (ORCID: https://orcid.org/0000-0002-0833-9493)
- František Babič (ORCID: https://orcid.org/0000-0003-2225-5955)
- Maroš Hliboký (ORCID: https://orcid.org/0000-0001-9693-8789)
- Marek Bundzel (ORCID: https://orcid.org/0000-0002-1319-1243)
- Martin Števík (ORCID: https://orcid.org/0000-0002-6824-5915)
- Michal Kolárik (ORCID: https://orcid.org/0000-0002-1835-6203)
- Martina Szabóová (ORCID: https://orcid.org/0000-0003-1245-0079)
- Štefánia Vetešková (ORCID: https://orcid.org/0000-0002-9162-9052)
- Marian Grendár (ORCID: https://orcid.org/0000-0002-6712-3457)
- Marek Malík (ORCID: https://orcid.org/0000-0001-7305-2897)
- Ján Magyar (ORCID: https://orcid.org/0000-0003-2149-0179)
- Kamil Zeleňák (ORCID: https://orcid.org/0000-0002-0416-2985)
- Viktória Máčajová
Institutions
- Technical University of Košice (SK)
- Martin University Hospital (SK)
- Comenius University Bratislava (SK)
Publication Details
- Journal
- PubMed
- Published
- 2024-08-12
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81