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build an ANN model through the neuralnet package by R language. Based on this algorithm, GSE98793 TestData 2 and independent blood GSE76826 were verified to correlate with MDD, with AUCs of 0.903 and 0.917, respectively. Conclusion To the best of our knowledge, this is the first time that the classifier constructed via DEG biomarkers be used as an endophenotype for MDD clinical diagnosis. Our results may provide a new entry point for the diagnosis, treatment, outcome prediction, prognosis and recurrence of MDD. Uterine Corpus Endometria
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