Transformers for rapid detection of airway stenosis and stridor
Abstract
Abstract Upper airway stenosis is a potentially life-threatening condition involving the narrowing of the airway. In more severe cases, airway stenosis may be accompanied by stridor, a type of disordered breathing caused by turbulent airflow. Patients with airway stenosis have a higher risk of airway failure and additional precautions must be taken before medical interventions like intubation. However, stenosis and stridor are often misdiagnosed as other respiratory conditions like asthma/wheezing, worsening outcomes. This report presents a unified dataset containing recorded breathing tasks from patients with stridor and airway stenosis. Customized transformer-based models were also trained to perform stenosis and stridor detection tasks using low-cost data from multiple acoustic prompts recorded on common devices. These methods achieved AUC scores of 0.875 for stenosis detection and 0.864 for stridor detection, demonstrating the potential to add value as screening tools in real-world clinical workflows, particularly in high-volume settings like emergency departments.
Article Details
Authors (36)
James Anibal
Rebecca Doctor
Micah Boyer
Karlee Newberry
Iris De Santiago
Shaheen Awan
Yassmeen Abdel-Aty
Gregory Dion
Veronica Daoud
Hannah Huth
Stephanie Watts
Bradford J. Wood
David Clifton
Alexander Gelbard
Maria Powell
Jamie Toghranegar
Olivier Elemento
Anais Rameau
Alexandros Sigaras
Satrajit Ghosh
Vardit Ravitsky
Jean Christophe Belisle-Pipon
David Dorr
Phillip Payne
Alistair Johnson
Ruth Bahr
Donald Bolser
Frank Rudzicz
Jordan Lerner Ellis
Jennifer Sui
Karim Hanna
Theresa Zesiewicz
Robin Zhao
Lochana Jayachandran
Samantha Salvi-Cruz
Yael Bensoussan