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Machine learning-based analysis of the digital pathology datasets for the predictive IHC panel Next, to identify the optimal number of protein combinations for predicting NAC responsiveness using clinically applicable IHC staining, the digital pathology datasets from the AMC NAC and PCT cohorts (Supplementary Tables 2 and 3) were analyzed using deep learning techniques similar to those used in transcriptome cross-validation modeling

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We note a 18-C decrease of the apparent T m for h SI-TGP after purification (Fig

doi: 10.3389/fmicb.2017.01531 368 ZhangF.LiD.YangY.ZhangH.ZhuJ.LiuJ.et al

Di Nicola M, Barteselli G, DellArti L et al (2015) Functional and structural abnormalities in deferoxamine retinopathy: a review of the literature

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