guest ::
| 001 | 843936 | ||
| 005 | 20251008164546.0 | ||
| 024 | 7 | _ | |2 ISSN |a 0309-0167 |
| 024 | 7 | _ | |2 ISSN |a 1365-2559 |
| 024 | 7 | _ | |2 SCOPUS |a SCOPUS:2-s2.0-85129878621 |
| 024 | 7 | _ | |2 WOS |a WOS:000793547800001 |
| 024 | 7 | _ | |2 doi |a 10.1111/his.14659 |
| 024 | 7 | _ | |2 datacite_doi |a 10.18154/RWTH-2022-03527 |
| 037 | _ | _ | |a RWTH-2022-03527 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |0 P:(DE-82)847314 |a Heinz, Céline N. |b 0 |u rwth |
| 245 | _ | _ | |a The future of artificial intelligence in digital pathology – results of a survey across stakeholder groups |h online, print |
| 260 | _ | _ | |a Oxford [u.a.] |b Wiley-Blackwell |c 2022 |
| 336 | 7 | _ | |0 0 |2 EndNote |a Journal Article |
| 336 | 7 | _ | |0 PUB:(DE-HGF)16 |2 PUB:(DE-HGF) |a Journal Article |b journal |m journal |
| 336 | 7 | _ | |2 BibTeX |a ARTICLE |
| 336 | 7 | _ | |2 DRIVER |a article |
| 336 | 7 | _ | |2 DataCite |a Output Types/Journal article |
| 336 | 7 | _ | |2 ORCID |a JOURNAL_ARTICLE |
| 536 | _ | _ | |0 G:(DE-82)X021000-OA |a OA - Open Access Publikation mit Unterstützung der Universitätsbibliothek der RWTH Aachen University (X021000-OA) |c X021000-OA |x 0 |
| 536 | _ | _ | |0 G:(DE-82)BMG-ZMVI1-2520DAT111 |a BMG-ZMVI1-2520DAT111 - Diagnosestellung und Risikostratifizierung von Lebererkrankungen mittels Deep Learning anhand von klinischen Routinedaten (DEEP LIVER) (BMG-ZMVI1-2520DAT111) |c BMG-ZMVI1-2520DAT111 |x 1 |
| 536 | _ | _ | |0 G:(DE-82)Stiftung-Deutsche-Krebshilfe-70113864 |a Max-Eder-Nachwuchsgruppenprogramm - Optimierung von Immuntherapie-Strategien bei gastrointestinalen Tumoren mit prädiktiven und mechanistischen Computermodellen (Stiftung-Deutsche-Krebshilfe-70113864) |c Stiftung-Deutsche-Krebshilfe-70113864 |x 2 |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: publications.rwth-aachen.de |
| 591 | _ | _ | |a Germany |
| 591 | _ | _ | |a Japan |
| 591 | _ | _ | |a UK |
| 700 | 1 | _ | |0 P:(DE-82)847315 |a Echle, Amelie |b 1 |u rwth |
| 700 | 1 | _ | |a Foersch, Sebastian |b 2 |
| 700 | 1 | _ | |0 0000-0002-4203-5696 |a Bychkov, Andrey |b 3 |
| 700 | 1 | _ | |0 P:(DE-82)765716 |a Kather, Jakob N. |b 4 |e Corresponding author |u rwth |
| 773 | _ | _ | |0 PERI:(DE-600)2006447-0 |a 10.1111/his.14659 |n 7 |p 1121-1127 |t Histopathology : journal of the British Division of the International Academy of Pathology |v 80 |x 0309-0167 |y 2022 |
| 856 | 4 | _ | |u https://publications.rwth-aachen.de/record/843936/files/843936.pdf |y OpenAccess |
| 876 | 7 | _ | |8 W-2022-01008-c |9 2025-08-28 |c 1834.29 |d 2022-04-04 |e Hybrid-OA |j DEAL |v 257.44 |
| 909 | C | O | |o oai:publications.rwth-aachen.de:843936 |p dnbdelivery |p openCost |p VDB |p driver |p OpenAPC_DEAL |p open_access |p openaire |
| 910 | 1 | _ | |0 I:(DE-588b)36225-6 |6 P:(DE-82)847314 |a RWTH Aachen |b 0 |k RWTH |
| 910 | 1 | _ | |0 I:(DE-588b)36225-6 |6 P:(DE-82)847315 |a RWTH Aachen |b 1 |k RWTH |
| 910 | 1 | _ | |0 I:(DE-588b)36225-6 |6 P:(DE-82)765716 |a RWTH Aachen |b 4 |k RWTH |
| 914 | 1 | _ | |y 2022 |
| 915 | 1 | _ | |0 StatID:(DE-HGF)0031 |2 StatID |a Peer reviewed article |x 0 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0150 |2 StatID |a DBCoverage |b Web of Science Core Collection |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0300 |2 StatID |a DBCoverage |b Medline |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)1030 |2 StatID |a DBCoverage |b Current Contents - Life Sciences |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)1190 |2 StatID |a DBCoverage |b Biological Abstracts |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0600 |2 StatID |a DBCoverage |b Ebsco Academic Search |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0100 |2 StatID |a JCR |b HISTOPATHOLOGY : 2019 |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)3001 |2 StatID |a DEAL Wiley |d 2021-01-29 |w ger |
| 915 | _ | _ | |0 StatID:(DE-HGF)0113 |2 StatID |a WoS |b Science Citation Index Expanded |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)9900 |2 StatID |a IF < 5 |d 2021-01-29 |
| 915 | _ | _ | |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |a Creative Commons Attribution CC BY 4.0 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0510 |2 StatID |a OpenAccess |
| 915 | _ | _ | |0 StatID:(DE-HGF)0030 |2 StatID |a Peer Review |b ASC |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)1050 |2 StatID |a DBCoverage |b BIOSIS Previews |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0160 |2 StatID |a DBCoverage |b Essential Science Indicators |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0200 |2 StatID |a DBCoverage |b SCOPUS |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)1110 |2 StatID |a DBCoverage |b Current Contents - Clinical Medicine |d 2021-01-29 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0420 |2 StatID |a Nationallizenz |d 2021-01-29 |w ger |
| 915 | _ | _ | |0 StatID:(DE-HGF)0199 |2 StatID |a DBCoverage |b Clarivate Analytics Master Journal List |d 2021-01-29 |
| 915 | p | c | |0 PC:(DE-HGF)0001 |2 APC |a Local Funding |
| 915 | p | c | |0 PC:(DE-HGF)0002 |2 APC |a DFG OA Publikationskosten |
| 915 | p | c | |0 PC:(DE-HGF)0000 |2 APC |a APC keys set |
| 915 | p | c | |0 PC:(DE-HGF)0120 |2 APC |a DEAL: Wiley 2019 |
| 920 | 1 | _ | |0 I:(DE-82)531030-2_20140620 |k 531030-2 |l Klinik und Lehrstuhl für Innere Medizin (mit dem Schwerpunkt Gastroenterologie und Stoffwechselkrankheiten) |x 0 |
| 980 | 1 | _ | |a APC |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a APC |
| 980 | _ | _ | |a I:(DE-82)531030-2_20140620 |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a journal |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|