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Multinomial analysis reveals associations between CT features and interstitial lung disease patterns, suggesting improved diagnostic accuracy.
Associations between individual radiologic features and interstitial lung disease patterns in a single multinomial model, reflective of multidimensional clinical reasoning, showed that radiologists emphasize disease distribution and distinctive features when identifying patterns.
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Marinescu et al. (2026) studied this question.
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