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The latest episode of Lungcast explores the evolving field of pulmonary imaging technology and the transformative impact of artificial intelligence.
0:15 Intro
1:10 The history of medical imaging technology
3:02 Artificial intelligence terminology
8:56 Use of AI to assess asthma airway and mucus changes
13:02 Imaging biomarkers for ILD
16:52 Using AI to observe longterm decline of lung function
21:00 Dysanapsis analysis through CT scans
24:04 Xenon-enhanced MRIs for microstructural lung abnormalities
28:50 How will AI us continue to evolve in pulmonology?
31:58 Outro
Artificial intelligence (AI) and machine learning has taken many industries including medicine by storm in only the last few years. Thought leaders, researchers and entire institutions are racing to determine the most optimal utility of AI while also seeking its limitations.
Though the questions of both its potential and pitfalls still remain relatively unanswered, some experts have found absolute benefit from its application already.
In the September 2024 episode of Lungcast, Rachel Eddy, PhD, assistant professor in the departments of radiology and pediatrics at the University of British Columbia, and an investigator at the BC Children’s Hospital, joins to guide listeners through the current and future uses of AI in lung imaging.
Lungcast is a monthly respiratory health podcast series hosted by Albert Rizzo, MD, chief medical officer of the American Lung Association (ALA), and produced by HCPLive and the ALA.
Through the 30-minute episode, Rizzo and Eddy review a number of functions and ongoing research catered to the use of AI in imaging—from the analysis of the effect of asthma on airway and mucus changes, to ongoing research into gradual lung health decline through air quality exposure.
Eddy also provides a prognosis on the next half-decade of AI application in pulmonary medicine, and highlights some of the most promising tools driving imaging research today.
Subscribe to Lungcast on Spotify here, or listen to the episode below.
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