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.

Journal: Neuro endocrinology letters
Published Date: Aug 12, 2024

Abstract

OBJECTIVES: Lung ultrasound reduces the number of chest X-rays after thoracic surgery and thus the radiation. COVID-19 pandemic has accelerated research in lung ultrasound artifacts detection using artificial intelligence. This study evaluates the accuracy of artificial intelligence in A-lines detection in thoracic surgery patients using a novel hybrid solution that combines convolutional neural networks and analytical approach and compares it with a radiology resident and radiology experts' results.

Authors

  • Martin Števík
    Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Marek Malík
    Department of Thoracic Surgery, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Štefánia Vetešková
    Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Zuzana Trabalková
    Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Maroš Hliboký
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • Michal Kolárik
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • Ján Magyar
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • Marek Bundzel
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • Martina Szabóová
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • František Babič
    Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, 040 01 Košice, Slovakia.
  • Marián Grendár
    Biomedical Centre Martin - BioMed Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Malá hora 4, 036 01, Martin, Slovakia.
  • Kamil Zeleňák
    Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Viktória Máčajová
    Clinic of Radiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Beáta Drobná Sániová
    Department of Anesthesiology and Intensive Medicine, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.
  • Anton Dzian
    Department of Thoracic Surgery, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Kollárova 2, 036 59 Martin, Slovakia.

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