Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy.
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| Title: | Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy. |
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| Authors: | Guleria S; Rush University Medical Center, Chicago, IL, USA., Shah TU; Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA, USA.; Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, VA, USA., Pulido JV; Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.; Department of Systems & Information Engineering, University of Virginia, Charlottesville, VA, USA., Fasullo M; Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA, USA.; Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, VA, USA., Ehsan L; Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, VA, USA., Lippman R; Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA, USA., Sali R; Department of Systems & Information Engineering, University of Virginia, Charlottesville, VA, USA., Mutha P; Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA, USA.; Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, VA, USA., Cheng L; Rush University Medical Center, Chicago, IL, USA., Brown DE; Department of Systems & Information Engineering, University of Virginia, Charlottesville, VA, USA., Syed S; Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, VA, USA. ss8xj@virginia.edu. |
| Source: | Scientific reports [Sci Rep] 2021 Mar 03; Vol. 11 (1), pp. 5086. Date of Electronic Publication: 2021 Mar 03. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-021-84510-4 |
