• 9: Simplifying Chest X-ray Diagnosis with AI

  • Oct 24 2023
  • Length: 26 mins
  • Podcast

9: Simplifying Chest X-ray Diagnosis with AI cover art

9: Simplifying Chest X-ray Diagnosis with AI

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  • Summary

  • In this month's episode of the Paper Club Podcast, your hosts Rafael Herrera and Sónia Marques welcome a special guest, Joana Rocha, a PhD candidate at the University of Porto's Engineering School. Joana joins us to discuss her seminal paper, 'Attention Driven Spatial Transformer Network for Abnormality Detection in Chest X-ray Images,' for which she is the lead author.

    The paper introduces a groundbreaking approach to computer-aided diagnosis in the medical field, specifically focusing on chest X-ray images. Unlike traditional methods that often require two separate models—one for selecting the thoracic region and another for the actual classification of abnormalities—the paper presents an end-to-end architecture that simplifies this process. 

    During the podcast, we explore the challenges and necessities of implementing AI models in healthcare. Joana's model addresses these by not only improving diagnostic performance but also offering insights into what the model is focusing on. This is crucial in a clinical setting, where understanding the model's decision-making process can be a matter of life and death. The model's ability to focus on the relevant anatomical features ensures that it gains the trust of medical professionals, a critical factor for its effective implementation in clinical practice.

    We thank Joana and her co-authors for developing this month’s paper. If you are interested in reading the paper for yourself, please check this link: https://ieeexplore.ieee.org/abstract/document/9867115  

    For more information on all things artificial intelligence, machine learning, and engineering for your business, please visit www.deeperinsights.com or reach out to us at thepaperclub@deeperinsights.com.
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