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.
Martin ŠtevíkMarek MalíkAnton DzianŠtefánia VeteškováZuzana TrabalkováMaroš HlibokýMichal KolárikJán MagyarMarek BundzelMartina SzabóováFrantišek BabičMarián GrendárKamil ZeleňákViktória MáčajováBeáta Drobná SániováPublished in: Neuro endocrinology letters (2024)
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.
Keyphrases
- artificial intelligence
- machine learning
- deep learning
- end stage renal disease
- thoracic surgery
- big data
- newly diagnosed
- ejection fraction
- chronic kidney disease
- convolutional neural network
- magnetic resonance imaging
- peritoneal dialysis
- prognostic factors
- patient safety
- computed tomography
- patient reported outcomes
- loop mediated isothermal amplification
- quantum dots
- sensitive detection
- contrast enhanced ultrasound
- solid state