Interpretation of chest X-rays and lung CT scan images using AI

Although artificial intelligence (AI) is still a developing field in many healthcare domains, initial applications and proof-of-concept studies have shown promising and impactful results in diagnosing different disease conditions using only raw data sources like diagnostic imaging.1 This episode will explore how AI can help interpret images, mainly CT scans and X-rays, to diagnose respiratory conditions better.2-4

References:

  1. San José Estépar, R. Functional imaging of the lung special feature: review article. Br J Radiol. 2022. Available at: https://doi.org/10.1259/bjr.2021052  
  2. Herrmann P, Busana M, Cressoni M, Lotz J, Moerer O, Saager L, et al. Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome. Front Physiol. 2021;12:676118. Available at: ⁠https://doi.org/10.3389/FPHYS.2021.676118⁠ 
  3. Seyyed-Kalantari L, Zhang H, McDermott MBA, Chen IY, Ghassemi M. Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations. Nat Med. 2021;27:2176-2182. Available at: ⁠https://doi.org/10.1038/s41591-021-01595-0⁠ 
  4. Jin KN, Kim EY, Kim YJ, Lee GP, Kim H, Oh S, et al. Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study. Eur Radiol. 2022;32:3469-3479. Available at: ⁠https://viatris-digitalassets.s3.eu-central-1.amazonaws.com/gr/general/Springer-RES-Diagnostic+effect+of+artificial+intelligence+solution+for+referable.pdf⁠ 

NON-2022-14800