Development and validation of an artificial intelligence algorithm for detecting vocal cords in video laryngoscopy.
Medicine (Baltimore)
; 102(51): e36761, 2023 Dec 22.
Article
en En
| MEDLINE
| ID: mdl-38134083
ABSTRACT
Airway procedures in life-threatening situations are vital for saving lives. Video laryngoscopy (VL) is commonly performed during endotracheal intubation (ETI) in the emergency department. Artificial intelligence (AI) is widely used in the medical field, particularly to detect anatomical structures. This study aimed to develop an AI algorithm that detects vocal cords from VL images acquired during emergent situations. This retrospective study used VL images acquired in the emergency department to facilitate the ETI. The vocal cord image was labeled with a ground-truth bounding box. The dataset was divided into training and validation datasets. The algorithm was developed from a training dataset using the YOLOv4 model. The performance of the algorithm was evaluated using a test set. The test set was further divided into specific environments during the ETI for clinical subgroup analysis. In total, 20,161 images from 84 patients were used in this study. A total of 10,287, 5766, and 4108 images were used for the model training, validation, and test sets, respectively. The developed algorithm achieved F1 score 0.906, sensitivity 0.963, and specificity 0.842 in the validation set. The performance in the test set was F1 score 0.808, sensitivity 0.823, and specificity 0.804. We developed and validated an AI algorithm to detect vocal cords in VL. This algorithm demonstrated a high performance. The algorithm can be used to determine the vocal cord to ensure safe ETI.
Texto completo:
1
Colección:
01-internacional
Asunto principal:
Pliegues Vocales
/
Inteligencia Artificial
Límite:
Humans
Idioma:
En
Revista:
Medicine (Baltimore)
Año:
2023
Tipo del documento:
Article