David Gutman to Reproducibility of Results
This is a "connection" page, showing publications David Gutman has written about Reproducibility of Results.
Connection Strength
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Applicability of digital analysis and imaging technology in neuropathology assessment. Neuropathology. 2016 Jun; 36(3):270-82.
Score: 0.088
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Somatic mutations associated with MRI-derived volumetric features in glioblastoma. Neuroradiology. 2015 Dec; 57(12):1227-37.
Score: 0.086
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MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set. Radiology. 2013 May; 267(2):560-9.
Score: 0.072
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Mapping of the mouse olfactory system with manganese-enhanced magnetic resonance imaging and diffusion tensor imaging. Brain Struct Funct. 2013 Mar; 218(2):527-37.
Score: 0.069
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Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge. Lancet Digit Health. 2022 05; 4(5):e330-e339.
Score: 0.034
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Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group. JAMA Dermatol. 2022 Jan 01; 158(1):90-96.
Score: 0.034
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Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers. Cancer Res. 2021 02 15; 81(4):1171-1177.
Score: 0.031
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Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study. Lancet Oncol. 2019 07; 20(7):938-947.
Score: 0.028
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Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features. Sci Rep. 2015 Nov 18; 5:16822.
Score: 0.022
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Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients. J Neuroradiol. 2015 Jul; 42(4):212-21.
Score: 0.020