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Algorithm outperforms radiologists at diagnosing pneumonia | Stanford News

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Stanford researchers have developed an algorithm that offers diagnoses based off chest X-ray images. It can diagnose up to 14 types of medical conditions and is able to diagnose pneumonia better than expert radiologists working alone.

A tool the researchers developed along with the algorithm produced these images, which are similar to heat maps and show the areas of the X-ray most indicative of pneumonia.

“Interpreting X-ray images to diagnose pathologies like pneumonia is very challenging, and we know that there’s a lot of variability in the diagnoses radiologists arrive at,” said Pranav Rajpurkar, a graduate student in the Stanford Machine Learning Group and co-lead author of the paper.

Within a week the researchers had an algorithm that diagnosed 10 of the pathologies labeled in the X-rays more accurately than previous state-of-the-art results. In that short time span, CheXNet also outperformed the four Stanford radiologists in diagnosing pneumonia accurately.

After about a month of continuous iteration, the algorithm outperformed the four individual Stanford radiologists in pneumonia diagnoses.


Article originally posted at

Post Author: Laura Sanders

2 thoughts on “Algorithm outperforms radiologists at diagnosing pneumonia | Stanford News

    Karl Lundqvist

    (January 23, 2018 - 8:46 pm)

    Margareta Jensen

    Marthy Ravello

    (January 23, 2018 - 8:46 pm)

    Pierre Ghiglino Perez

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