Figure 2 | Scientific Reports

Figure 2

From: Radiologists can visually predict mortality risk based on the gestalt of chest radiographs comparable to a deep learning network

Figure 2

Representative cases from the training data set: in the training data set, image findings (diagnostic and subclinical) as well as gestalt of the image (defined as the degree of deviation from an unremarkable chest radiograph associated with the likelihood of 6-year mortality rated on a binary scale) were assessed. In row (A), both participants presented with emphysema, indicating that a single major diagnostic finding are not reliable predictors for outcome. In row (B), 13 findings were reported in image on left, 4 findings were reported in image on right; example that sum of findings per subject was not associated with mortality. In row (C), image on left surgical clips indicate elevated probability of dying, however, radiologists rated gestalt of the image as “absent” on left and as “present” on right.

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