Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2026-03-26 @ 3:14 PM
Ignite Modification Date:
2026-03-26 @ 3:14 PM
NCT ID:
NCT07411495
Brief Summary:
We're developing a new AI, which uses advanced computer technology to help doctors identify patients who might have a difficult airway before surgery or emergency procedures. Sometimes, when a person needs help breathing, doctors have to insert a tube into their airway. This can be challenging for some people due to the shape of their mouth, throat, or neck. We hope that AI will look at a patient's facial features to predict if there might be any difficulties.
Detailed Description:
AINFAS (Artificial Intelligence-enabled system for airway assessment) is an innovative AI system we're developing to revolutionize airway management in healthcare. This advanced artificial intelligence is designed to analyze patient characteristics and predict potential difficulties in airway management before any medical procedure that might require breathing assistance. Using sophisticated machine learning algorithms, AINFAS processes data such as facial structure and neck anatomy to assess the likelihood of a difficult airway. This non-invasive, rapid assessment tool has potential applications across various healthcare settings, including pre-operative assessments, emergency departments, intensive care units, and even pre-hospital care. By providing early identification of potential airway challenges, AINFAS aims to enhance patient safety, improve resource allocation, and provide a standardized, objective method of airway assessment. Currently in development and testing, this AI system represents a significant step forward in using technology to enhance clinical decision-making and patient safety in critical aspects of medical care.
Study:
NCT07411495
Study Brief:
Protocol Section:
NCT07411495