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Skip search results from other journals and go to results- 463 Journal of Medical Internet Research
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Lin et al [10] evaluated 12 distinctive images per specialty and demonstrated no significant differences between the AAMC residency data and the ethnic makeup of AI -generated faces. Their results are inconsistent with our data where we instead demonstrated a significant difference in gender among 12/19 specialties when comparing AI-generated images to AAMC residency data.
JMIR AI 2025;4:e56891
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The Boruta algorithm identifies the most salient features by comparing the Z-value of each feature with that of the “shadow feature.” The Z-value of each attribute is obtained from the random forest model at each iteration by copying all the real features and shuffling them sequentially. In contrast, the Z-value of the shadow is generated by randomly shuffling the real features.
J Med Internet Res 2025;27:e67258
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WHO growth standards were used to calculate age- and sex-specific weight-for-age z scores at birth and around the age of 1 year, and the difference between the two time points was calculated. RWG during infancy was defined as a change in weight-for-age z score>0.67, which is clinically equivalent to upward crossing one centile line in a weight growth chart [14,15].
A range of prenatal and early postnatal factors were collected across all the cohorts.
JMIR Public Health Surveill 2025;11:e69220
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