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Artificial Intelligence Helps Otolaryngologists Give Excellent Patient Care

by Jennifer Fink • January 18, 2023

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Artificial intelligence systems may also help clarify which patients are at increased risk of lymph node metastasis and are therefore good candidates for elective neck dissection. Dr. Bur led a multi-institutional team that developed and validated an AI system that could predict occult nodal metastasis with a significantly higher degree of accuracy as compared with tumor depth thresholds that are commonly used in clinical practice. The system had a sensitivity of 91.7%, specificity of 72.6%, positive predictive value of 39.3%, and negative predictive value of 97.8% (JAMA Netw Open. 2022;5:e227226. doi:10.1001/jamanetworkopen. 2022.7226).

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Explore This Issue
January 2023

Jonathan Garneau, MD, assistant professor of otolaryngology–head and neck surgery at the University of Virginia School of Medicine in Charlottesville, is investigating whether artificial intelligence can use computerized tomography (CT) images to predict the risk of metastasis. Computers can detect patterns and features that the human eye cannot detect, so AI may help clinicians extract more meaningful information from a CT scan. This additional information may eventually allow physicians to more effectively determine which patients require surgery, and which can be treated with other modalities.

“If we can develop machine learning models that are highly accurate, patients who are at low risk may not need to undergo any neck surgery,” Dr. Bur added.

Diagnosing Infection and Predicting Aspiration with Vocal Data

During the COVID-19 pandemic, researchers wondered if it might be possible to use cough sounds to detect COVID-19 disease. Scientists at the Massachusetts Institute of Technology in Cambridge developed an AI model that attempted to distinguish people with asymptomatic COVID- 19 from healthy individuals through forced-cough recordings submitted via computers and cell phones (Chu J. Artificial intelligence model detects asymptomatic Covid-19 infections through cellphone-recorded coughs. MIT News. October 29, 2020), and in April 2022, Pfizer submitted a $75 million offer to purchase an Australian digital health company that created a smartphone-based app that can analyze the sound of a cough and diagnose respiratory diseases, including asthma, pneumonia, croup, and COVID-19 (Schuster-Bruce C. A health firm says it has developed an app that can detect COVID-19 when an infected person coughs into their phone. Insider. April 19, 2022). Pfizer finalized its acquisition of the company in a $116 million deal announced at the end of September 2022.

Anaïs Rameau, MD, a laryngologist, chief of dysphagia at the Sean Parker Institute for the Voice, and assistant professor and director of new technologies in the department of otolaryngology–head and neck surgery at Weill Cornell Medical College in New York City, has received the prestigious Paul B. Beeson Emerging Leaders Career Development Award in Aging from the National Institute on Aging to create an AI-based clinical decision support tool to improve the detection of aspiration risk at the bedside, using a combination of voice and cough sound and clinical and demographic data. “We’re looking at different aspects of their voice, such as changes in voice quality after drinking water, to determine whether that can help us distinguish who’s at risk for aspiration,” Dr. Rameau said, noting that speech–language pathologists aren’t always available to provide instrumental swallowing studies in the outpatient setting, such as nursing homes. The clinical decision support tool will be app-based and will be driven by AI algorithms to process complex multi-modal data and help improve the reliability of the bedside swallow screen.

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Filed Under: Features, Home Slider Tagged With: diagnosis, medical technology, patient careIssue: January 2023

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