Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Maria Gabrani"'
Autor:
M. Emre Sahin, Benjamin C. B. Symons, Pushpak Pati, Fayyaz Minhas, Declan Millar, Maria Gabrani, Stefano Mensa, Jan Lukas Robertus
Publikováno v:
Quantum, Vol 8, p 1502 (2024)
Quantum machine learning with quantum kernels for classification problems is a growing area of research. Recently, quantum kernel alignment techniques that parameterise the kernel have been developed, allowing the kernel to be trained and therefore a
Externí odkaz:
https://doaj.org/article/e1fda2ab68dc4dc0b4b35b9d9474797e
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
Externí odkaz:
https://doaj.org/article/3c7aac54d7e44a9586f0ed1a2f9a763c
Autor:
Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V. Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L. Shah, Emmanouil Karteris, Jan L. Robertus, Maria Gabrani, Michal Rosen-Zvi
Publikováno v:
Patterns, Vol 2, Iss 6, Pp 100269- (2021)
Summary: Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear. We conducted the largest systematic review of the literature addressing the utility of AI in imaging for
Externí odkaz:
https://doaj.org/article/96dfaf7a0d8346f788dd6f9f30ca030c
Autor:
Andreea Anghel, Milos Stanisavljevic, Sonali Andani, Nikolaos Papandreou, Jan Hendrick Rüschoff, Peter Wild, Maria Gabrani, Haralampos Pozidis
Publikováno v:
Frontiers in Medicine, Vol 6 (2019)
Stain normalization is an important processing task for computer-aided diagnosis (CAD) systems in modern digital pathology. This task reduces the color and intensity variations present in stained images from different laboratories. Consequently, stai
Externí odkaz:
https://doaj.org/article/928ced48664f47e9b014964c9425d9bb
Publikováno v:
Frontiers in Medicine, Vol 6 (2019)
Clinical morphological analysis of histopathology samples is an effective method in cancer diagnosis. Computational pathology methods can be employed to automate this analysis, providing improved objectivity and scalability. More specifically, comput
Externí odkaz:
https://doaj.org/article/b48a8c664a1744079f8c9b374ff5d35e
Autor:
Kevin Thandiackal, Boqi Chen, Pushpak Pati, Guillaume Jaume, Drew F. K. Williamson, Maria Gabrani, Orcun Goksel
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198021
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60b6bb51180f0a565532e3118789d0fd
https://doi.org/10.1007/978-3-031-19803-8_41
https://doi.org/10.1007/978-3-031-19803-8_41
Autor:
Pushpak Pati, Guillaume Jaume, Antonio Foncubierta-Rodriguez, Florinda Feroce, Giosue Scognamiglio, Anna Maria Anniciello, Nadia Brancati, Maria Frucci, Daniel Riccio, Jean-Philippe Thiran, Orcun Goksel, Maria Gabrani
Publikováno v:
Artificial Intelligence Applications in Human Pathology, edited by Huss, Ralf; Grunkin, Michael., pp. 243–285. Londra: World Scientific Publishing, 2022
info:cnr-pdr/source/autori:P. Pati, G. Jaume, A. Foncubierta-Rodriguez, F. Feroce, G. Scognamiglio, A. M. Anniciello, N. Brancati, M. Frucci, D. Riccio, J.-P. Thiran, O. Goksel, M. Gabrani/titolo:Graph representation learning & explainability in breast cancer pathology: bridging the gap between AI and pathology practice/titolo_volume:Artificial Intelligence Applications in Human Pathology/curatori_volume:Huss, Ralf; Grunkin, Michael./editore: /anno:2022
info:cnr-pdr/source/autori:P. Pati, G. Jaume, A. Foncubierta-Rodriguez, F. Feroce, G. Scognamiglio, A. M. Anniciello, N. Brancati, M. Frucci, D. Riccio, J.-P. Thiran, O. Goksel, M. Gabrani/titolo:Graph representation learning & explainability in breast cancer pathology: bridging the gap between AI and pathology practice/titolo_volume:Artificial Intelligence Applications in Human Pathology/curatori_volume:Huss, Ralf; Grunkin, Michael./editore: /anno:2022
While cancer cases continue to increase and diagnosis, prognosis and treatment become more digital, AI-assisted cancer patient care, in particular in the pathology daily practice, remains scarce and rudimentary. In this chapter, we focus on reducing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2dc3510f7f563ed4b649c99b95190fbd
https://publications.cnr.it/doc/463064
https://publications.cnr.it/doc/463064
Autor:
Hung-Chun Hsu, Hung-Wen Tsai, Maria Gabrani, Pau-Choo Chung, Antonio Foncubierta Rodriguez, Yu-Ting Wu
Publikováno v:
2021 IEEE Symposium Series on Computational Intelligence (SSCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1fac669eba0ce2c10b7ab960187d24d
https://doi.org/10.1109/ssci50451.2021.9659856
https://doi.org/10.1109/ssci50451.2021.9659856
Autor:
Orcun Goksel, Nuri Murat Arar, Anna Fomitcheva Khartchenko, Pushpak Pati, Govind V. Kaigala, Aditya Kashyap, Maria Gabrani
Publikováno v:
IEEE Transactions on Biomedical Engineering, 66 (10)
IEEE Transactions on Biomedical Engineering, 66 (10)
ISSN:0018-9294
ISSN:1558-2531
ISSN:0018-9294
ISSN:1558-2531
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ed1427e3a24615bd55f08f5dd3e4226
https://doi.org/10.1109/tbme.2019.2899156
https://doi.org/10.1109/tbme.2019.2899156