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Velupillai et al [23] explained that although such systems may show high performances in intrinsic evaluation, they may have reduced value at the higher patient level. When the abovementioned problem-oriented NLP models are viewed through the lens of the well-defined model of patient-centered health care [9], they appear to be analogous to disease-oriented, evidence-based medicine models, as they focus on a particular disease or problem instead of holistically taking patients into account.
JMIR Med Inform 2021;9(9):e18471
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We used the Twitter word clusters, “50mpaths2,” provided by Owoputi et al [41]. For the advanced classifiers, each word or character sequence was replaced with a dense vector, and the vectors were then fed into the relevant algorithms for training.
We performed hyperparameter tuning using the validation set to improve the classification task on the imbalanced data set. Specifically, we focused on improving the F1 score for consumer feedback.
J Med Internet Res 2021;23(5):e26616
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