One paper, published by Springer — a deep-learning model that reads chest X-rays. The full citation, the abstract, and where to read it.
An improved deep-learning model for detecting and classifying lung diseases from X-ray images, advancing computer-aided diagnosis for pulmonary conditions with high accuracy and clinical interpretability.
Peer-reviewed book chapter
Springer
4
April 2025
Chest radiography is the most widely available thoracic imaging test in the world, and also one of the hardest to read consistently — the same film can produce different calls from different readers, and in much of the world there is no radiologist available to make the call at all. Computer-aided diagnosis is not about replacing that judgement; it is about giving it a second, tireless reader that flags what deserves a closer look.
Somewhere between software that can't fail and software that has to be believed is the engineer I'm becoming.
Generated from the published record. Author order follows the chapter listing.
Dr. Babu Kumar, Charan Reddy Chanda, et al. (2025). Lung Disease Detection and Classification with an Improved Deep Learning Model Using X-Ray Images. Springer. https://doi.org/10.1007/978-3-032-22289-3_35