Title: | Automated analysis of proliferating cells spatial organisation predicts prognosis in lung neuroendocrine neoplasms |
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Authors: | ID Bulloni, Matteo (Author) ID Sandrini, Giada (Author) ID Stacchiotti, Irene (Author) ID Barberis, M. (Author) ID Calabrese, Fiorella (Author) ID Carvalho, Lina (Author) ID Fontanini, Gabriella (Author) ID Alì, Greta (Author) ID Fortarezza, Francesco (Author) ID Hofman, Paul (Author) ID Kern, Izidor, Klinika Golnik (Author) |
Files: | URL - Source URL, visit https://www.mdpi.com/2072-6694/13/19/4875/pdf
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Language: | English |
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Typology: | 1.01 - Original Scientific Article |
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Organization: | UKPBAG - University Clinic of Respiratory and Allergic Diseases Golnik
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Keywords: | neuroendocrine tumors, lung neoplasms, carcinoma, prognosis, pathology, histology, Ki-67 antigen, machine learning, image enhancement, lung cancer, neuroendocrine neoplasms |
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Publication status: | Published |
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Publication version: | Version of Record |
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Place of publishing: | Švica |
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Publisher: | MDPI |
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Year of publishing: | 2021 |
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Number of pages: | str. 1-19 |
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Numbering: | Vol. 13, iss. 19 |
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PID: | 20.500.12556/DiRROS-14589 |
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UDC: | 616-006 |
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ISSN on article: | 2072-6694 |
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DOI: | 10.3390/cancers13194875 |
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COBISS.SI-ID: | 80161795 |
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Copyright: | © by the authors |
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Note: | Nasl. z nasl. zaslona;
Soavtor iz Slovenije: Izidor Kern;
Opis vira z dne 12. 10. 2021;
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Publication date in DiRROS: | 09.11.2021 |
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Views: | 1176 |
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Downloads: | 502 |
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