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  "Title": "Estimation of Accuracy in Multisite Machine-Learning Models",
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  "Description": "The effects of the site may severely bias the accuracy of\na multisite machine-learning model, even if the analysts\nremoved them when fitting the model in the 'training set' and\napplying the model in the 'test set' (Solanes et al.,\nNeuroimage 2023, 265:119800). This simple R package estimates\nthe accuracy of a multisite machine-learning model unbiasedly,\nas described in (Solanes et al., Psychiatry Research:\nNeuroimaging 2021, 314:111313). It currently supports the\nestimation of sensitivity, specificity, balanced accuracy (for\nbinary or multinomial variables), the area under the curve,\ncorrelation, mean squarer error, and hazard ratio for binomial,\nmultinomial, gaussian, and survival (time-to-event) outcomes.",
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