@article{DBLP:journals/bmcbi/MarchesinS22,
author = {Stefano Marchesin and
Gianmaria Silvello},
title = {{TBGA:} a large-scale Gene-Disease Association dataset for Biomedical
Relation Extraction},
journal = {{BMC} Bioinform.},
volume = {23},
number = {1},
pages = {111},
year = {2022},
url = {https://doi.org/10.1186/s12859-022-04646-6},
doi = {10.1186/s12859-022-04646-6},
timestamp = {Wed, 20 Apr 2022 10:08:38 +0200},
biburl = {https://dblp.org/rec/journals/bmcbi/MarchesinS22.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Marchesin, S., Silvello, G. TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation Extraction. BMC Bioinformatics 23, 111 (2022). https://doi.org/10.1186/s12859-022-04646-6
Alberto Purpura, Gian Antonio Susto:
A Bayesian Neural Model for Documents' Relevance Estimation. DESIRES 2021: 156-161
@inproceedings{DBLP:conf/desires/PurpuraS21,
author = {Alberto Purpura and
Gian Antonio Susto},
editor = {Omar Alonso and
Stefano Marchesin and
Marc Najork and
Gianmaria Silvello},
title = {A Bayesian Neural Model for Documents' Relevance Estimation},
booktitle = {Proceedings of the Second International Conference on Design of Experimental
Search {\&} Information REtrieval Systems, Padova, Italy, September
15-18, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2950},
pages = {156--161},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2950/paper-15.pdf},
timestamp = {Mon, 25 Oct 2021 15:03:55 +0200},
biburl = {https://dblp.org/rec/conf/desires/PurpuraS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Alberto Purpura, Karolina Buchner, Gianmaria Silvello, and Gian Antonio Susto
Alberto Purpura, Karolina Buchner, Gianmaria Silvello, Gian Antonio Susto:
Neural Feature Selection for Learning to Rank. ECIR (2) 2021: 342-349
@inproceedings{DBLP:conf/ecir/PurpuraBSS21,
author = {Alberto Purpura and
Karolina Buchner and
Gianmaria Silvello and
Gian Antonio Susto},
editor = {Djoerd Hiemstra and
Marie{-}Francine Moens and
Josiane Mothe and
Raffaele Perego and
Martin Potthast and
Fabrizio Sebastiani},
title = {Neural Feature Selection for Learning to Rank},
booktitle = {Advances in Information Retrieval - 43rd European Conference on {IR}
Research, {ECIR} 2021, Virtual Event, March 28 - April 1, 2021, Proceedings,
Part {II}},
series = {Lecture Notes in Computer Science},
volume = {12657},
pages = {342--349},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-72240-1\_34},
doi = {10.1007/978-3-030-72240-1\_34},
timestamp = {Fri, 14 May 2021 08:34:11 +0200},
biburl = {https://dblp.org/rec/conf/ecir/PurpuraBSS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Jeroen van der Laak, Geert Litjens and Francesco Ciompi
Deep learning in histopathology: the path to the clinic
Van der Laak J, Litjens G, Ciompi F. Deep learning in histopathology: the path to the clinic. Nature medicine. 2021 May;27(5):775-84.
@article{van2021deep,
title={Deep learning in histopathology: the path to the clinic},
author={Van der Laak, Jeroen and Litjens, Geert and Ciompi, Francesco},
journal={Nature medicine},
volume={27},
number={5},
pages={775--784},
year={2021},
publisher={Nature Publishing Group}
}
Fabio Giachelle, Ornella Irrera and Gianmaria Silvello
MedTAG: A Portable and Customizable Annotation Tool for Biomedical Documents
Anton Hristov, Aleksandar Tahchiev, Hristo Papazov, Nikola Tulechki, Todor Primov, Svetla Boytcheva:
Application of Deep Learning Methods to SNOMED CT Encoding of Clinical Texts: From Data Collection to Extreme Multi-Label Text-Based Classification. RANLP 2021: 557-565
@inproceedings{DBLP:conf/ranlp/HristovTPTPB21,
author = {Anton Hristov and
Aleksandar Tahchiev and
Hristo Papazov and
Nikola Tulechki and
Todor Primov and
Svetla Boytcheva},
editor = {Galia Angelova and
Maria Kunilovskaya and
Ruslan Mitkov and
Ivelina Nikolova{-}Koleva},
title = {Application of Deep Learning Methods to {SNOMED} {CT} Encoding of
Clinical Texts: From Data Collection to Extreme Multi-Label Text-Based
Classification},
booktitle = {Proceedings of the International Conference on Recent Advances in
Natural Language Processing {(RANLP} 2021), Held Online, 1-3September,
2021},
pages = {557--565},
publisher = {{INCOMA} Ltd.},
year = {2021},
url = {https://aclanthology.org/2021.ranlp-1.63},
timestamp = {Tue, 23 Nov 2021 15:10:57 +0100},
biburl = {https://dblp.org/rec/conf/ranlp/HristovTPTPB21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
G. Faggioli, S. Marchesin
What Makes a Query Semantically Hard?
Design of Experimental Search & Information REtrieval Systems (DESIRES 2021)
Guglielmo Faggioli, Stefano Marchesin:
What Makes a Query Semantically Hard? DESIRES 2021: 61-69
@inproceedings{DBLP:conf/desires/Faggioli021,
author = {Guglielmo Faggioli and
Stefano Marchesin},
editor = {Omar Alonso and
Stefano Marchesin and
Marc Najork and
Gianmaria Silvello},
title = {What Makes a Query Semantically Hard?},
booktitle = {Proceedings of the Second International Conference on Design of Experimental
Search {\&} Information REtrieval Systems, Padova, Italy, September
15-18, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2950},
pages = {61--69},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2950/paper-06.pdf},
timestamp = {Mon, 25 Oct 2021 15:03:55 +0200},
biburl = {https://dblp.org/rec/conf/desires/Faggioli021.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
M. Agosti, S. Marchesin, and G. Silvello
SAFIR: a Semantic-Aware Neural Framework for IR
11th Italian Information Retrieval Workshop (IIR 2021)
Maristella Agosti, Stefano Marchesin, Gianmaria Silvello:
SAFIR: a Semantic-Aware Neural Framework for IR. IIR 2021
@inproceedings{DBLP:conf/iir/Agosti0S21,
author = {Maristella Agosti and
Stefano Marchesin and
Gianmaria Silvello},
editor = {Vito Walter Anelli and
Tommaso Di Noia and
Nicola Ferro and
Fedelucio Narducci},
title = {{SAFIR:} a Semantic-Aware Neural Framework for {IR}},
booktitle = {Proceedings of the 11th Italian Information Retrieval Workshop 2021,
Bari, Italy, September 13-15, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2947},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2947/paper13.pdf},
timestamp = {Mon, 25 Oct 2021 15:03:55 +0200},
biburl = {https://dblp.org/rec/conf/iir/Agosti0S21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Niccoló Marini, Sebastian Otálora, Manfredo Atzori, Henning Müller
Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification
Niccolò Marini, Sebastian Otálora, Henning Müller, Manfredo Atzori,
Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification,
Medical Image Analysis,
Volume 73,
2021,
102165,
ISSN 1361-8415,
https://doi.org/10.1016/j.media.2021.102165.
(https://www.sciencedirect.com/science/article/pii/S1361841521002115)
@article{MARINI2021102165,
title = {Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification},
journal = {Medical Image Analysis},
volume = {73},
pages = {102165},
year = {2021},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2021.102165},
url = {https://www.sciencedirect.com/science/article/pii/S1361841521002115},
author = {Niccolò Marini and Sebastian Otálora and Henning Müller and Manfredo Atzori},
keywords = {Computational pathology, Deep learning, Semi-supervision, Prostate cancer},
}
Fabio Giachelle, Dennis Dosso and Gianmaria Silvello
NanoWeb: Search, Access and Explore Life Science Nanopublications on the Web (Extended Abstract).
Proc. 29th Italian Symposium on Advanced Database Systems (SEBD 2021)
@inproceedings{DBLP:conf/sebd/GiachelleDS21,
author = {Fabio Giachelle and
Dennis Dosso and
Gianmaria Silvello},
editor = {Sergio Greco and
Maurizio Lenzerini and
Elio Masciari and
Andrea Tagarelli},
title = {NanoWeb: Search, Access and Explore Life Science Nanopublications
on the Web (Discussion Paper)},
booktitle = {Proceedings of the 29th Italian Symposium on Advanced Database Systems,
{SEBD} 2021, Pizzo Calabro (VV), Italy, September 5-9, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2994},
pages = {506--513},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2994/paper58.pdf},
timestamp = {Fri, 12 Nov 2021 17:12:18 +0100},
biburl = {https://dblp.org/rec/conf/sebd/GiachelleDS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello and Gian Antonio Susto
Incentives for Item Duplication under Fair Ranking Policies
In Proc. of the 2nd International Workshop on Algorithmic Bias in Search and Recommendation (BIAS@ECIR2021)
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello, Gian Antonio Susto:
Incentives for Item Duplication Under Fair Ranking Policies. BIAS 2021: 64-77
@inproceedings{DBLP:conf/bias/NunzioFSS21,
author = {Giorgio Maria Di Nunzio and
Alessandro Fabris and
Gianmaria Silvello and
Gian Antonio Susto},
editor = {Ludovico Boratto and
Stefano Faralli and
Mirko Marras and
Giovanni Stilo},
title = {Incentives for Item Duplication Under Fair Ranking Policies},
booktitle = {Advances in Bias and Fairness in Information Retrieval - Second International
Workshop on Algorithmic Bias in Search and Recommendation, {BIAS}
2021, Lucca, Italy, April 1, 2021, Proceedings},
series = {Communications in Computer and Information Science},
volume = {1418},
pages = {64--77},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-78818-6\_7},
doi = {10.1007/978-3-030-78818-6\_7},
timestamp = {Fri, 02 Jul 2021 07:22:57 +0200},
biburl = {https://dblp.org/rec/conf/bias/NunzioFSS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Ornella Irrera and Gianmaria Silvello
Background Linking: Joining Entity Linking with Learning to Rank Models
Proc. of the 17th Italian Research Conference on Digital Libraries (IRCDL 2021)
Ornella Irrera and Gianmaria Silvello . Background Linking: Joining Entity Linking with Learning to Rank Models. Proc. of the 17th Italian Research Conference on Digital Libraries (IRCDL 2021). Ceur-WS Proceedings, Open Access, 2021.
@inproceedings{DBLP:conf/ircdl/IrreraS21,
author = {Ornella Irrera and
Gianmaria Silvello},
editor = {Dennis Dosso and
Stefano Ferilli and
Paolo Manghi and
Antonella Poggi and
Giuseppe Serra and
Gianmaria Silvello},
title = {Background Linking: Joining Entity Linking with Learning to Rank Models},
booktitle = {Proceedings of the 17th Italian Research Conference on Digital Libraries,
Padua, Italy (virtual event due to the Covid-19 pandemic), February
18-19, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2816},
pages = {64--77},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2816/paper6.pdf},
timestamp = {Mon, 01 Mar 2021 17:21:10 +0100},
biburl = {https://dblp.org/rec/conf/ircdl/IrreraS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Sebastian Otálora, Niccolo Marini, Henning Müller, and Manfredo Atzori.
Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
Mart van Rijthoven, Maschenka Balkenhol, Karina Silina, Jeroen van der Laak, Francesco Ciompi:
HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images. Medical Image Anal. 68: 101890 (2021)
@article{DBLP:journals/mia/RijthovenBSLC21,
author = {Mart van Rijthoven and
Maschenka Balkenhol and
Karina Silina and
Jeroen van der Laak and
Francesco Ciompi},
title = {HookNet: Multi-resolution convolutional neural networks for semantic
segmentation in histopathology whole-slide images},
journal = {Medical Image Anal.},
volume = {68},
pages = {101890},
year = {2021},
url = {https://doi.org/10.1016/j.media.2020.101890},
doi = {10.1016/j.media.2020.101890},
timestamp = {Tue, 01 Jun 2021 15:19:54 +0200},
biburl = {https://dblp.org/rec/journals/mia/RijthovenBSLC21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Dennis Dosso and Gianmaria Silvello
Data Credit Distribution through Lineage
Proc. of the 17th Italian Research Conference on Digital Libraries (IRCDL 2021)
Dennis Dosso, Gianmaria Silvello:
Data Credit Distribution through Lineage. IRCDL 2021: 155-161
@inproceedings{DBLP:conf/ircdl/DossoS21,
author = {Dennis Dosso and
Gianmaria Silvello},
editor = {Dennis Dosso and
Stefano Ferilli and
Paolo Manghi and
Antonella Poggi and
Giuseppe Serra and
Gianmaria Silvello},
title = {Data Credit Distribution through Lineage},
booktitle = {Proceedings of the 17th Italian Research Conference on Digital Libraries,
Padua, Italy (virtual event due to the Covid-19 pandemic), February
18-19, 2021},
series = {{CEUR} Workshop Proceedings},
volume = {2816},
pages = {155--161},
publisher = {CEUR-WS.org},
year = {2021},
url = {http://ceur-ws.org/Vol-2816/short3.pdf},
timestamp = {Mon, 01 Mar 2021 17:21:10 +0100},
biburl = {https://dblp.org/rec/conf/ircdl/DossoS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Fabio Giachelle, Dennis Dosso, Gianmaria Silvello
Search, access, and explore nanopublications on the Web
Fabio Giachelle, Dennis Dosso, Gianmaria Silvello:
Search, access, and explore life science nanopublications on the Web. PeerJ Comput. Sci. 7: e335 (2021)
@article{DBLP:journals/peerj-cs/GiachelleDS21,
author = {Fabio Giachelle and
Dennis Dosso and
Gianmaria Silvello},
title = {Search, access, and explore life science nanopublications on the Web},
journal = {PeerJ Comput. Sci.},
volume = {7},
pages = {e335},
year = {2021},
url = {https://doi.org/10.7717/peerj-cs.335},
doi = {10.7717/peerj-cs.335},
timestamp = {Tue, 09 Mar 2021 16:21:56 +0100},
biburl = {https://dblp.org/rec/journals/peerj-cs/GiachelleDS21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Witali Aswolinskiy, David Tellez, Gabriel Raya, Lieke van der Woude, Monika Looijen-Salamon, Jeroen van der Laak, Katrien Grünberg, Francesco Ciompi
Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images
Aswolinskiy W, Tellez D, Raya G, van der Woude L, Looijen-Salamon M, van der Laak J, Grunberg K, Ciompi F. Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images. InMedical Imaging 2021: Digital Pathology 2021 Feb 15 (Vol. 11603, p. 1160304). International Society for Optics and Photonics.
@inproceedings{aswolinskiy2021neural,
title={Neural image compression for non-small cell lung cancer subtype classification in H\&E stained whole-slide images},
author={Aswolinskiy, Witali and Tellez, David and Raya, Gabriel and van der Woude, Lieke and Looijen-Salamon, Monika and van der Laak, Jeroen and Grunberg, Katrien and Ciompi, Francesco},
booktitle={Medical Imaging 2021: Digital Pathology},
volume={11603},
pages={1160304},
year={2021},
organization={International Society for Optics and Photonics}
}
Mart van Rijthoven, Maschenka Balkenhol, Manfredo Atzori, Peter Bult, Jeroen van der Laak, and Francesco Ciompi
Few-shot weakly supervised detection and retrieval in histopathology whole-slide images
van Rijthoven M, Balkenhol M, Atzori M, Bult P, van der Laak J, Ciompi F. Few-shot weakly supervised detection and retrieval in histopathology whole-slide images. InMedical Imaging 2021: Digital Pathology 2021 Feb 15 (Vol. 11603, p. 116030N). International Society for Optics and Photonics.
@inproceedings{van2021few,
title={Few-shot weakly supervised detection and retrieval in histopathology whole-slide images},
author={van Rijthoven, Mart and Balkenhol, Maschenka and Atzori, Manfredo and Bult, Peter and van der Laak, Jeroen and Ciompi, Francesco},
booktitle={Medical Imaging 2021: Digital Pathology},
volume={11603},
pages={116030N},
year={2021},
organization={International Society for Optics and Photonics}
}
Niccolo Marini, Sebastian Otalora, Henning Muller, and Manfredo Atzori
Semi-supervised learning with a teacher-student paradigm for histopathology classification: a resource to face data heterogeneity and lack of local annotations
Niccolò Marini, Sebastian Otálora, Henning Müller, Manfredo Atzori:
Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local Annotations. ICPR Workshops (1) 2020: 105-119
@inproceedings{DBLP:conf/icpr/MariniOMA20,
author = {Niccol{\`{o}} Marini and
Sebastian Ot{\'{a}}lora and
Henning M{\"{u}}ller and
Manfredo Atzori},
editor = {Alberto Del Bimbo and
Rita Cucchiara and
Stan Sclaroff and
Giovanni Maria Farinella and
Tao Mei and
Marco Bertini and
Hugo Jair Escalante and
Roberto Vezzani},
title = {Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology
Classification: {A} Resource to Face Data Heterogeneity and Lack of
Local Annotations},
booktitle = {Pattern Recognition. {ICPR} International Workshops and Challenges
- Virtual Event, January 10-15, 2021, Proceedings, Part {I}},
series = {Lecture Notes in Computer Science},
volume = {12661},
pages = {105--119},
publisher = {Springer},
year = {2020},
url = {https://doi.org/10.1007/978-3-030-68763-2\_9},
doi = {10.1007/978-3-030-68763-2\_9},
timestamp = {Tue, 23 Feb 2021 11:44:59 +0100},
biburl = {https://dblp.org/rec/conf/icpr/MariniOMA20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Anjani Dhrangadhariya, Sebastian Otalora, Manfredo Atzori, and Henning Muller
Classification of noisy free-text prostate cancer pathology reports using natural language processing
Anjani Dhrangadhariya, Sebastian Otálora, Manfredo Atzori, Henning Müller:
Classification of Noisy Free-Text Prostate Cancer Pathology Reports Using Natural Language Processing. ICPR Workshops (1) 2020: 154-166
@inproceedings{DBLP:conf/icpr/DhrangadhariyaO20,
author = {Anjani Dhrangadhariya and
Sebastian Ot{\'{a}}lora and
Manfredo Atzori and
Henning M{\"{u}}ller},
editor = {Alberto Del Bimbo and
Rita Cucchiara and
Stan Sclaroff and
Giovanni Maria Farinella and
Tao Mei and
Marco Bertini and
Hugo Jair Escalante and
Roberto Vezzani},
title = {Classification of Noisy Free-Text Prostate Cancer Pathology Reports
Using Natural Language Processing},
booktitle = {Pattern Recognition. {ICPR} International Workshops and Challenges
- Virtual Event, January 10-15, 2021, Proceedings, Part {I}},
series = {Lecture Notes in Computer Science},
volume = {12661},
pages = {154--166},
publisher = {Springer},
year = {2020},
url = {https://doi.org/10.1007/978-3-030-68763-2\_12},
doi = {10.1007/978-3-030-68763-2\_12},
timestamp = {Tue, 23 Mar 2021 14:14:21 +0100},
biburl = {https://dblp.org/rec/conf/icpr/DhrangadhariyaO20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Giorgio Maria Di Nunzio
As Simple as Possible: Using the R Tidyverse for Multilingual Information Extraction
Giorgio Maria Di Nunzio:
As Simple as Possible: Using the R Tidyverse for Multilingual Information Extraction. IMS UniPD ad CLEF eHealth 2020 Task 1. CLEF (Working Notes) 2020
@inproceedings{DBLP:conf/clef/Nunzio20,
author = {Giorgio Maria Di Nunzio},
editor = {Linda Cappellato and
Carsten Eickhoff and
Nicola Ferro and
Aur{\'{e}}lie N{\'{e}}v{\'{e}}ol},
title = {As Simple as Possible: Using the {R} Tidyverse for Multilingual Information
Extraction. {IMS} UniPD ad {CLEF} eHealth 2020 Task 1},
booktitle = {Working Notes of {CLEF} 2020 - Conference and Labs of the Evaluation
Forum, Thessaloniki, Greece, September 22-25, 2020},
series = {{CEUR} Workshop Proceedings},
volume = {2696},
publisher = {CEUR-WS.org},
year = {2020},
url = {http://ceur-ws.org/Vol-2696/paper\_137.pdf},
timestamp = {Tue, 27 Oct 2020 17:12:48 +0100},
biburl = {https://dblp.org/rec/conf/clef/Nunzio20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Giorgio Maria Di Nunzio, , Stefano Marchesin, and Federica Vezzani
A Study on Reciprocal Ranking Fusion in Consumer Health Search
Giorgio Maria Di Nunzio, Stefano Marchesin, Federica Vezzani:
A Study on Reciprocal Ranking Fusion in Consumer Health Search. IMS UniPD ad CLEF eHealth 2020 Task 2. CLEF (Working Notes) 2020
@inproceedings{DBLP:conf/clef/Nunzio0V20,
author = {Giorgio Maria Di Nunzio and
Stefano Marchesin and
Federica Vezzani},
editor = {Linda Cappellato and
Carsten Eickhoff and
Nicola Ferro and
Aur{\'{e}}lie N{\'{e}}v{\'{e}}ol},
title = {A Study on Reciprocal Ranking Fusion in Consumer Health Search. {IMS}
UniPD ad {CLEF} eHealth 2020 Task 2},
booktitle = {Working Notes of {CLEF} 2020 - Conference and Labs of the Evaluation
Forum, Thessaloniki, Greece, September 22-25, 2020},
series = {{CEUR} Workshop Proceedings},
volume = {2696},
publisher = {CEUR-WS.org},
year = {2020},
url = {http://ceur-ws.org/Vol-2696/paper\_128.pdf},
timestamp = {Tue, 27 Oct 2020 17:12:48 +0100},
biburl = {https://dblp.org/rec/conf/clef/Nunzio0V20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Stefano Marchesin
Developing Unsupervised Knowledge-Enhanced Models to Reduce the Semantic Gap in Information Retrieval
Ph.D. Thesis at the University of Padua
2020
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Maristella Agosti, Stefano Marchesin and Gianmaria Silvello
Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval
Agosti M., Marchesin S., Silvello G. Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval. ACM Transactions on Information Systems. 2020 Jul;1(1) pp. 48.
@article{agosti2020learning,
title={Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval},
author={Agosti, M. and Marchesin, S. and Silvello, G.},
journal={ACM Transactions on Information Systems},
volume={1},
number={1},
year={2020}
}
Dennis Dosso, Gianmaria Silvello
Data Credit Distribution: A New Method to Estimate Databases Impact
@incollection{otalora2020semi,
title={Semi-weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks},
author={Ot{\'a}lora, Sebastian and Marini, Niccol{\`o} and M{\"u}ller, Henning and Atzori, Manfredo},
booktitle={Interpretable and Annotation-Efficient Learning for Medical Image Computing},
pages={193--203},
year={2020},
publisher={Springer}
}
Federica Vezzani, Giorgio Maria Di Nunzio
Methodology for the standardization of terminological resources: the design of the TriMED database for supporting multi-register medical communication
Vezzani F, Di Nunzio GM. On the Formal Standardization of Terminology Resources: The Case Study of TriMED. InProceedings of The 12th Language Resources and Evaluation Conference 2020 May (pp. 4903-4910).
@inproceedings{vezzani2020formal,
title={On the Formal Standardization of Terminology Resources: The Case Study of TriMED},
author={Vezzani, Federica and Di Nunzio, Giorgio Maria},
booktitle={Proceedings of The 12th Language Resources and Evaluation Conference},
pages={4903--4910},
year={2020}
}
David Tellez, Diederik Hoppener, Cornelis Verhoef, Dirk Grunhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
Tellez D, Hoppener D, Verhoef C, Grunhagen D, Nierop P, Drozdzal M, van der Laak J, Ciompi F. Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. arXiv preprint arXiv:2004.07041. 2020 Apr 15.
@article{tellez2020extending,
title={Extending Unsupervised Neural Image Compression With Supervised Multitask Learning},
author={Tellez, David and Hoppener, Diederik and Verhoef, Cornelis and Grunhagen, Dirk and Nierop, Pieter and Drozdzal, Michal and van der Laak, Jeroen and Ciompi, Francesco},
journal={arXiv preprint arXiv:2004.07041},
year={2020}
}
Maristella Agosti, Giorgio Maria Di Nunzio, Stefano Marchesin
A Post-Analysis of Query Reformulation Methods for Clinical Trials Retrieval (discussion paper)
Agosti, Maristella, Giorgio Maria Di Nunzio, and Stefano Marchesin. "A Post-Analysis of Query Reformulation Methods for Clinical Trials Retrieval." Proceedings of the 28th Italian Symposium on Advanced Database Systems, pg. 152-159
@inproceedings{DBLP:conf/sebd/AgostiN020,
author = {Maristella Agosti and
Giorgio Maria Di Nunzio and
Stefano Marchesin},
editor = {Maristella Agosti and
Maurizio Atzori and
Paolo Ciaccia and
Letizia Tanca},
title = {A Post-Analysis of Query Reformulation Methods for Clinical Trials
Retrieval},
booktitle = {Proceedings of the 28th Italian Symposium on Advanced Database Systems,
Villasimius, Sud Sardegna, Italy (virtual due to Covid-19 pandemic),
June 21-24, 2020},
series = {{CEUR} Workshop Proceedings},
volume = {2646},
pages = {152--159},
publisher = {CEUR-WS.org},
year = {2020},
url = {http://ceur-ws.org/Vol-2646/13-paper.pdf},
timestamp = {Tue, 11 Aug 2020 17:34:11 +0200},
biburl = {https://dblp.org/rec/conf/sebd/AgostiN020.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Dennis Dosso, Gianmaria Silvello
A Document-based RDF Keyword Search System: Query-by-Query Analysis
Dosso D, Silvello G. A Document-based RDF Keyword Search System: Query-by-Query Analysis. Proceedings of the 28th Italian Symposium on Advanced Database Systems
Villasimius, Sud Sardegna, Italy (virtual due to Covid-19 pandemic), June 21-24, 2020. pg. 67-79
@inproceedings{DBLP:conf/sebd/DossoS20,
author = {Dennis Dosso and
Gianmaria Silvello},
editor = {Maristella Agosti and
Maurizio Atzori and
Paolo Ciaccia and
Letizia Tanca},
title = {A Document-based {RDF} Keyword Search System: Query-by-Query Analysis},
booktitle = {Proceedings of the 28th Italian Symposium on Advanced Database Systems,
Villasimius, Sud Sardegna, Italy (virtual due to Covid-19 pandemic),
June 21-24, 2020},
series = {{CEUR} Workshop Proceedings},
volume = {2646},
pages = {68--79},
publisher = {CEUR-WS.org},
year = {2020},
url = {http://ceur-ws.org/Vol-2646/19-paper.pdf},
timestamp = {Tue, 11 Aug 2020 17:34:11 +0200},
biburl = {https://dblp.org/rec/conf/sebd/DossoS20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Sebastian Otálora, Oscar Jimenez-del-Toro, Manfredo Atzori, Amjad Khan, Vincent Andrearczyk, Henning Müller
A systematic comparison of deep learning strategies for weakly supervised Gleason grading.
Otálora S, Atzori M, Khan A, Jimenez-del-Toro O, Andrearczyk V, Müller H. A systematic comparison of deep learning strategies for weakly supervised Gleason grading. InMedical Imaging 2020: Digital Pathology 2020 Mar 16 (Vol. 11320, p. 113200L). International Society for Optics and Photonics.
@inproceedings{otalora2020systematic,
title={A systematic comparison of deep learning strategies for weakly supervised Gleason grading},
author={Ot{\'a}lora, Sebastian and Atzori, Manfredo and Khan, Amjad and Jimenez-del-Toro, Oscar and Andrearczyk, Vincent and M{\"u}ller, Henning},
booktitle={Medical Imaging 2020: Digital Pathology},
volume={11320},
pages={113200L},
year={2020},
organization={International Society for Optics and Photonics}
}
Anjani K. Dhrangadhariya, Oscar Jimenez-del-Toro, Vincent Andrearczyk, Manfredo Atzori and Henning Müller
Exploiting the biomedical literature to mine out a large multimodal dataset of rare cancer studies
Dhrangadhariya A, Jimenez-del-Toro O, Andrearczyk V, Atzori M, Müller H. Exploiting biomedical literature to mine out a large multimodal dataset of rare cancer studies. InMedical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications 2020 Mar 2 (Vol. 11318, p. 113180A). International Society for Optics and Photonics.
@inproceedings{dhrangadhariya2020exploiting,
title={Exploiting biomedical literature to mine out a large multimodal dataset of rare cancer studies},
author={Dhrangadhariya, Anjani and Jimenez-del-Toro, Oscar and Andrearczyk, Vincent and Atzori, Manfredo and M{\"u}ller, Henning},
booktitle={Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications},
volume={11318},
pages={113180A},
year={2020},
organization={International Society for Optics and Photonics}
}
Amjad Khan, Manfredo Atzori, Sebastian Otálora, Vincent Andrearczyk and Henning Müller
Generalizing convolution neural networks on stain color heterogeneous data for computational pathology
Khan A, Atzori M, Otálora S, Andrearczyk V, Müller H. Generalizing convolution neural networks on stain color heterogeneous data for computational pathology. InMedical Imaging 2020: Digital Pathology 2020 Mar 16 (Vol. 11320, p. 113200R). International Society for Optics and Photonics.
@inproceedings{khan2020generalizing,
title={Generalizing convolution neural networks on stain color heterogeneous data for computational pathology},
author={Khan, Amjad and Atzori, Manfredo and Ot{\'a}lora, Sebastian and Andrearczyk, Vincent and M{\"u}ller, Henning},
booktitle={Medical Imaging 2020: Digital Pathology},
volume={11320},
pages={113200R},
year={2020},
organization={International Society for Optics and Photonics}
}
Henning Müller, Vincent Andrearczyk, Oscar Jimenez-del-Toro, Anjani Dhrangadhariya, Roger Schaer and Manfredo Atzori
Studying Publicly Available Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction
Müller H, Andrearczyk V, del Toro OJ, Dhrangadhariya A, Schaer R, Atzori M. Studying Public Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction. InInternational Conference on Multimedia Modeling 2020 Jan 5 (pp. 553-564). Springer, Cham.
@inproceedings{muller2020studying,
title={Studying Public Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction},
author={M{\"u}ller, Henning and Andrearczyk, Vincent and del Toro, Oscar Jimenez and Dhrangadhariya, Anjani and Schaer, Roger and Atzori, Manfredo},
booktitle={International Conference on Multimedia Modeling},
pages={553--564},
year={2020},
organization={Springer}
}
Dennis Dosso ; Gianmaria Silvello
Search Text to Retrieve Graphs: A Scalable RDF Keyword-Based Search System
Dosso D, Silvello G. Search Text to Retrieve Graphs: A Scalable RDF Keyword-Based Search System. IEEE Access. 2020 Jan 15;8:14089-111.
@article{dosso2020search,
title={Search Text to Retrieve Graphs: A Scalable RDF Keyword-Based Search System},
author={Dosso, Dennis and Silvello, Gianmaria},
journal={IEEE Access},
volume={8},
pages={14089--14111},
year={2020},
publisher={IEEE}
}
Giorgio Maria Di Nunzio, Stefano Marchesin, Maristella Agosti
Exploring how to Combine Query Reformulations for Precision Medicine
Precision Medicine Track, The Text Retrieval Conference (TREC 2019), NIST, Gaithersburg, Md. USA, 13-15 November 2019
Di Nunzio GM, Marchesin S, Agosti M. Exploring how to Combine Query Reformulations for Precision Medicine. InTREC 2019.
@inproceedings{di2019exploring,
title={Exploring how to Combine Query Reformulations for Precision Medicine.},
author={Di Nunzio, Giorgio Maria and Marchesin, Stefano and Agosti, Maristella},
booktitle={TREC},
year={2019}
}
Stefano Marchesin, Alberto Purpura and Gianmaria Silvello
Focal Elements of Neural Information Retrieval Models. An Outlook through a Reproducibility Study
Marchesin, S., Purpura, A., & Silvello, G. (2019). Focal elements of neural information retrieval models. An outlook through a reproducibility study. Information Processing & Management, 102109.
Bibtex:
@article{marchesin2019focal,
title={Focal elements of neural information retrieval models. An outlook through a reproducibility study},
author={Marchesin, Stefano and Purpura, Alberto and Silvello, Gianmaria},
journal={Information Processing \& Management},
pages={102109},
year={2019},
publisher={Elsevier}
}
D. Tellez, G. Litjens, P. Bandi, W. Bulten, J. Bokhorst, F. Ciompi and J. van der Laak
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
Tellez D, Litjens G, Bándi P, Bulten W, Bokhorst JM, Ciompi F, van der Laak J. Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. Medical image analysis. 2019 Dec 1;58:101544.
@article{DBLP:journals/mia/TellezLBBBCL19,
author = {David Tellez and
Geert Litjens and
P{\'{e}}ter B{\'{a}}ndi and
Wouter Bulten and
John{-}Melle Bokhorst and
Francesco Ciompi and
Jeroen van der Laak},
title = {Quantifying the effects of data augmentation and stain color normalization
in convolutional neural networks for computational pathology},
journal = {Medical Image Anal.},
volume = {58},
year = {2019},
url = {https://doi.org/10.1016/j.media.2019.101544},
doi = {10.1016/j.media.2019.101544},
timestamp = {Thu, 23 Jul 2020 11:01:20 +0200},
biburl = {https://dblp.org/rec/journals/mia/TellezLBBBCL19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
Neural Image Compression for Gigapixel Histopathology Image Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, DOI: 10.1109/TPAMI.2019.2936841
Tellez, D., Litjens, G., van der Laak, J., & Ciompi, F. (2019). Neural Image Compression for Gigapixel Histopathology Image Analysis. IEEE transactions on pattern analysis and machine intelligence.
@article{tellez2019neural,
title={Neural Image Compression for Gigapixel Histopathology Image Analysis},
author={Tellez, David and Litjens, Geert and van der Laak, Jeroen and Ciompi, Francesco},
journal={IEEE transactions on pattern analysis and machine intelligence},
year={2019},
publisher={IEEE}
}
G. Litjens, F. Ciompi, J. Wolterink, B. de Vos, T. Leiner, J. Teuwen and I. Isgum
State-of-the-Art Deep Learning in Cardiovascular Image Analysis
Litjens, G., Ciompi, F., Wolterink, J.M., de Vos, B.D., Leiner, T., Teuwen, J. and Išgum, I., 2019. State-of-the-art deep learning in cardiovascular image analysis. JACC: Cardiovascular Imaging, 12(8), pp.1549-1565.
@article{litjens2019state,
title={State-of-the-art deep learning in cardiovascular image analysis},
author={Litjens, Geert and Ciompi, Francesco and Wolterink, Jelmer M and de Vos, Bob D and Leiner, Tim and Teuwen, Jonas and I{\v{s}}gum, Ivana},
journal={JACC: Cardiovascular Imaging},
volume={12},
number={8},
pages={1549--1565},
year={2019},
publisher={Elsevier}
}
Zaneta Swiderska-Chadaj
et al. Hans Pinckaers, Mart van Rijthoven, Maschenka Balkenhol, Margarita Melnikova, Oscar Geessink, Quirine Manson, Mark Sherman, António Polónia, Jeremy Parry, Mustapha Abubakar, Geert J. S. Litjens, Jeroen van der Laak, Francesco Ciompi
Learning to detect lymphocytes in immunohistochemistry with deep learning
Swiderska-Chadaj, Zaneta, et al. "Learning to detect lymphocytes in immunohistochemistry with deep learning." Medical image analysis 58 (2019): 101547.
@article{swiderska2019learning,
title={Learning to detect lymphocytes in immunohistochemistry with deep learning},
author={Swiderska-Chadaj, Zaneta and Pinckaers, Hans and van Rijthoven, Mart and Balkenhol, Maschenka and Melnikova, Margarita and Geessink, Oscar and Manson, Quirine and Sherman, Mark and Polonia, Antonio and Parry, Jeremy and others},
journal={Medical image analysis},
volume={58},
pages={101547},
year={2019},
publisher={Elsevier}
}
John-Melle Bokhorst
et al. Hans Pinckaers, Peter van Zwam, Iris Nagtegaal, Jeroen van der Laak, Francesco Ciompi
Learning from sparsely annotated data for semantic segmentation in histopathology images
Bokhorst, John-Melle, et al. "Learning from sparsely annotated data for semantic segmentation in histopathology images." (2018).
@inproceedings{DBLP:conf/midl/BokhorstPZNLC19,
author = {John{-}Melle Bokhorst and
Hans Pinckaers and
Peter van Zwam and
Iris Nagtegaal and
Jeroen van der Laak and
Francesco Ciompi},
title = {Learning from sparsely annotated data for semantic segmentation in
histopathology images},
booktitle = {{MIDL}},
series = {Proceedings of Machine Learning Research},
volume = {102},
pages = {84--91},
publisher = {{PMLR}},
year = {2019}
}
Alberto Purpura, Marco Maggipinto, Gianmaria Silvello, Gian Antonio Susto
Probabilistic Word Embeddings in Neural IR: A Promising Model That Does Not Work as Expected (For Now)
The 5th ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2019)
Alberto Purpura, Marco Maggipinto, Gianmaria Silvello, Gian Antonio Susto:
Probabilistic Word Embeddings in Neural IR: A Promising Model That Does Not Work as Expected (For Now). ICTIR 2019: 3-10
@inproceedings{DBLP:conf/ictir/PurpuraMSS19,
author = {Alberto Purpura and
Marco Maggipinto and
Gianmaria Silvello and
Gian Antonio Susto},
title = {Probabilistic Word Embeddings in Neural {IR:} {A} Promising Model
That Does Not Work as Expected (For Now)},
booktitle = {{ICTIR}},
pages = {3--10},
publisher = {{ACM}},
year = {2019}
}
Erika Fabris, Tobias Kuhn, Gianmaria Silvello
A Framework for Citing Nanopublications
23rd International Conference on Theory and Practice of Digital Libraries (TPDL 2019)
Dosso, Dennis. "A Keyword Search and Citation System for RDF Graphs." FDIA@ESSIR (2019) 23-28.
@inproceedings{DBLP:conf/fdia/Dosso19,
author = {Dennis Dosso},
editor = {Ingo Frommholz and
Haiming Liu and
Yashar Moshfeghi},
title = {A Keyword Search and Citation System for {RDF} Graphs},
booktitle = {Proceedings of the 9th PhD Symposium on Future Directions in Information
Access co-located with 12th European Summer School in Information
Retrieval {(ESSIR} 2019), Milan, Italy, July 17th - to - 18th, 2019},
series = {{CEUR} Workshop Proceedings},
volume = {2537},
pages = {23--28},
publisher = {CEUR-WS.org},
year = {2019},
url = {http://ceur-ws.org/Vol-2537/paper-05.pdf},
timestamp = {Wed, 12 Feb 2020 16:44:32 +0100},
biburl = {https://dblp.org/rec/conf/fdia/Dosso19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Dennis Dosso, Gianmaria Silvello
A Scalable Virtual Document-Based Keyword Search System for RDF Datasets
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2019), July 21-25, 2019, Paris, France
Dennis Dosso, Gianmaria Silvello:
A Scalable Virtual Document-Based Keyword Search System for RDF Datasets. SIGIR 2019: 965-968
@inproceedings{DBLP:conf/sigir/DossoS19,
author = {Dennis Dosso and
Gianmaria Silvello},
title = {A Scalable Virtual Document-Based Keyword Search System for {RDF}
Datasets},
booktitle = {{SIGIR}},
pages = {965--968},
publisher = {{ACM}},
year = {2019}
}
Maristella Agosti, Giorgio Maria Di Nunzio, Stefano Marchesin
An Analysis of Query Reformulation Techniques for Precision Medicine
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2019), July 21-25, 2019, Paris, France
Maristella Agosti, Giorgio Maria Di Nunzio, Stefano Marchesin:
An Analysis of Query Reformulation Techniques for Precision Medicine. SIGIR 2019: 973-976
@inproceedings{DBLP:conf/sigir/AgostiN019,
author = {Maristella Agosti and
Giorgio Maria Di Nunzio and
Stefano Marchesin},
title = {An Analysis of Query Reformulation Techniques for Precision Medicine},
booktitle = {{SIGIR}},
pages = {973--976},
publisher = {{ACM}},
year = {2019}
}
Maristella Agosti, Giorgio Maria Di Nunzio, Stefano Marchesin, Gianmaria Silvello
Medical Retrieval using Structured Information Extracted from Knowledge Bases
Proceedings of the 27th Italian Symposium on Advanced Database Systems (SEBD 2019), June 16-19, 2019, Castiglione della Pescaia, Italy
Maristella Agosti, Giorgio Maria Di Nunzio, Stefano Marchesin, Gianmaria Silvello:
Medical Retrieval using Structured Information Extracted from Knowledge Bases. SEBD 2019
@inproceedings{DBLP:conf/sebd/AgostiN0S19,
author = {Maristella Agosti and
Giorgio Maria Di Nunzio and
Stefano Marchesin and
Gianmaria Silvello},
title = {Medical Retrieval using Structured Information Extracted from Knowledge
Bases},
booktitle = {{SEBD}},
series = {{CEUR} Workshop Proceedings},
volume = {2400},
publisher = {CEUR-WS.org},
year = {2019}
}
Roger Schaer, Sebastian Otálora, Oscar Jimenez del Toro, Manfredo Atzori and Henning Müller
Deep learning based retrieval system for gigapixel histopathology cases and open access literature
Schaer, Roger, et al. "Deep learning-based retrieval system for gigapixel histopathology cases and the open access literature." Journal of pathology informatics 10 (2019).
@article{schaer2019deep,
title={Deep learning-based retrieval system for gigapixel histopathology cases and the open access literature},
author={Schaer, Roger and Ot{\'a}lora, Sebastian and Jimenez-del-Toro, Oscar and Atzori, Manfredo and M{\"u}ller, Henning},
journal={Journal of pathology informatics},
volume={10},
year={2019},
publisher={Wolters Kluwer--Medknow Publications}
}
Stefano Marchesin
Knowledge Enhanced Representations to Reduce the Semantic Gap in Clinical Decision Support
9th PhD Symposium on Future Directions in Information Access (FDIA 2019), 2019
Marchesin, Stefano. "Knowledge Enhanced Representations to Reduce the Semantic Gap in Clinical Decision Support."FDIA@ESSIR 2019, 4-9
@article{marchesinknowledge,
title={Knowledge Enhanced Representations to Reduce the Semantic Gap in Clinical Decision Support},
author={Marchesin, Stefano}
}
Stefano Marchesin and Maristella Agosti
Knowledge Enhanced Representations for Clinical Decision Support
Proceedings of the 10th Italian Information Retrieval Workshop, CEUR Workshop Proceedings, Vol. 2441, pages 17-18
Otálora S, Atzori M, Andrearczyk V, Khan A, Müller H. Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology. Frontiers in Bioengineering and Biotechnology. 2019;7:198.
@article{otalora2019staining,
title={Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology},
author={Ot{\'a}lora, Sebastian and Atzori, Manfredo and Andrearczyk, Vincent and Khan, Amjad and M{\"u}ller, Henning},
journal={Frontiers in Bioengineering and Biotechnology},
volume={7},
pages={198},
year={2019},
publisher={Frontiers}
}
