Παρακολούθηση
Stefano Marchesin
Stefano Marchesin
Università degli Studi di Padova
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα dei.unipd.it - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations
N Marini, S Marchesin, S Otálora, M Wodzinski, A Caputo, ...
NPJ digital medicine 5 (1), 102, 2022
54*2022
Focal elements of neural information retrieval models. An outlook through a reproducibility study
S Marchesin, A Purpura, G Silvello
Information Processing & Management 57 (6), 102109, 2020
362020
Learning unsupervised knowledge-enhanced representations to reduce the semantic gap in information retrieval
M Agosti, S Marchesin, G Silvello
ACM Transactions on Information Systems (TOIS) 38 (4), 1-48, 2020
332020
TBGA: a large-scale gene-disease association dataset for biomedical relation extraction
S Marchesin, G Silvello
BMC bioinformatics 23 (1), 111, 2022
312022
Multi-scale task multiple instance learning for the classification of digital pathology images with global annotations
N Marini, S Otálora, F Ciompi, G Silvello, S Marchesin, S Vatrano, ...
MICCAI Workshop on Computational Pathology, 170-181, 2021
262021
An analysis of query reformulation techniques for precision medicine
M Agosti, GM Di Nunzio, S Marchesin
Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019
252019
Query performance prediction for neural IR: Are we there yet?
G Faggioli, T Formal, S Marchesin, S Clinchant, N Ferro, B Piwowarski
European Conference on Information Retrieval, 232-248, 2023
242023
Empowering digital pathology applications through explainable knowledge extraction tools
S Marchesin, F Giachelle, N Marini, M Atzori, S Boytcheva, G Buttafuoco, ...
Journal of pathology informatics 13, 100139, 2022
222022
Overview of iDPP@ CLEF 2023: the intelligent disease progression prediction challenge
G Faggioli, A Guazzo, S Marchesin, L Menotti, I Trescato, A Helena, ...
CEUR WORKSHOP PROCEEDINGS 3497, 1123-1164, 2023
212023
The university of padua ims research group at trec 2018 precision medicine track
M Agosti, G DI NUNZIO, S Marchesin
Proceedings of the Twenty-Seventh Text REtrieval Conference, TREC 2018, 2018
192018
Exploring how to Combine Query Reformulations for Precision Medicine.
GM Di Nunzio, S Marchesin, M Agosti
TREC, 2019
132019
Intelligent disease progression prediction: overview of iDPP@ CLEF 2023
G Faggioli, A Guazzo, S Marchesin, L Menotti, I Trescato, H Aidos, ...
International Conference of the Cross-Language Evaluation Forum for European …, 2023
112023
Towards query performance prediction for neural information retrieval: challenges and opportunities
G Faggioli, T Formal, S Lupart, S Marchesin, S Clinchant, N Ferro, ...
Proceedings of the 2023 ACM SIGIR International Conference on Theory of …, 2023
102023
What makes a query semantically hard?
G Faggioli, S Marchesin
CEUR WORKSHOP PROCEEDINGS 2950, 61-69, 2021
102021
Intelligent disease progression prediction: overview of iDPP@ CLEF 2024
G Birolo, P Bosoni, G Faggioli, H Aidos, R Bergamaschi, P Cavalla, ...
International Conference of the Cross-Language Evaluation Forum for European …, 2024
92024
Searching for reliable facts over a medical knowledge base
F Giachelle, S Marchesin, G Silvello, O Alonso
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
92023
Caption generation from histopathology whole-slide images using pre-trained transformers
BC Guevara, N Marini, S Marchesin, W Aswolinskiy, RJ Schlimbach, ...
Medical Imaging with Deep Learning, short paper track, 2023
92023
Overview of idpp@ clef 2024: the intelligent disease progression prediction challenge
G Birolo, P Bosoni, G Faggioli, H Aidos, R Bergamaschi, P Cavalla, ...
Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024 …, 2024
82024
A Docker-Based Replicability Study of a Neural Information Retrieval Model.
N Ferro, S Marchesin, A Purpura, G Silvello
OSIRRC@ SIGIR 2409, 37-43, 2019
82019
A relation extraction approach for clinical decision support
M Agosti, GM Di Nunzio, S Marchesin, G Silvello
arXiv preprint arXiv:1905.01257, 2019
82019
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