David Gutman to Machine Learning
This is a "connection" page, showing publications David Gutman has written about Machine Learning.
Connection Strength
1.684
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Validation of machine learning models to detect amyloid pathologies across institutions. Acta Neuropathol Commun. 2020 04 28; 8(1):59.
Score: 0.656
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Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers. Cancer Res. 2021 02 15; 81(4):1171-1177.
Score: 0.171
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Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells. Lab Invest. 2020 01; 100(1):98-109.
Score: 0.158
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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: 0.154
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Digital imaging applications and informatics in dermatology. Semin Cutan Med Surg. 2019 Mar 01; 38(1):E43-E48.
Score: 0.151
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Interactive phenotyping of large-scale histology imaging data with HistomicsML. Sci Rep. 2017 11 06; 7(1):14588.
Score: 0.138
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The status of digital pathology and associated infrastructure within Alzheimer's Disease Centers. J Neuropathol Exp Neurol. 2023 02 21; 82(3):202-211.
Score: 0.050
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An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears. Mod Pathol. 2023 Feb; 36(2):100003.
Score: 0.049
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NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer. Gigascience. 2022 05 17; 11.
Score: 0.047
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Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples. Histopathology. 2021 May; 78(6):791-804.
Score: 0.044
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Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images. J Am Acad Dermatol. 2018 02; 78(2):270-277.e1.
Score: 0.034
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Multi-scale classification based lesion segmentation for dermoscopic images. Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug; 2016:1361-1364.
Score: 0.032