Zobrazeno 1 - 10
of 147
pro vyhledávání: '"Giuseppe Jurman"'
Autor:
Simone Monaco, Nicole Bussola, Sara Buttò, Diego Sona, Flavio Giobergia, Giuseppe Jurman, Christodoulos Xinaris, Daniele Apiletti
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Autosomal dominant polycystic kidney disease (ADPKD) is a monogenic, rare disease, characterized by the formation of multiple cysts that grow out of the renal tubules. Despite intensive attempts to develop new drugs or repurpose existing one
Externí odkaz:
https://doaj.org/article/697e7ac4757d4de2b8f1248c5b9ee9de
Autor:
Massimiliano Datres, Elisa Paolazzi, Marco Chierici, Matteo Pozzi, Antonio Colangelo, Marcello Dorian Donzella, Giuseppe Jurman
Publikováno v:
BioData Mining, Vol 16, Iss 1, Pp 1-12 (2023)
Abstract Background Discrimination between patients affected by inflammatory bowel diseases and healthy controls on the basis of endoscopic imaging is an challenging problem for machine learning models. Such task is used here as the testbed for a nov
Externí odkaz:
https://doaj.org/article/2c7743d3d6c34865880ae4ff6e4dc1fb
Publikováno v:
BioData Mining, Vol 16, Iss 1, Pp 1-16 (2023)
Abstract Neuroblastoma is a childhood neurological tumor which affects hundreds of thousands of children worldwide, and information about its prognosis can be pivotal for patients, their families, and clinicians. One of the main goals in the related
Externí odkaz:
https://doaj.org/article/6f222d1a6a7b4cd2adba369f65775510
Autor:
Davide Chicco, Giuseppe Jurman
Publikováno v:
BioData Mining, Vol 16, Iss 1, Pp 1-12 (2023)
Abstract Bioinformatics has become a key aspect of the biomedical research programmes of many hospitals’ scientific centres, and the establishment of bioinformatics facilities within hospitals has become a common practice worldwide. Bioinformaticia
Externí odkaz:
https://doaj.org/article/cef4ada2418640c7a73b242ade83f707
Autor:
Davide Chicco, Giuseppe Jurman
Publikováno v:
BioData Mining, Vol 16, Iss 1, Pp 1-23 (2023)
Abstract Binary classification is a common task for which machine learning and computational statistics are used, and the area under the receiver operating characteristic curve (ROC AUC) has become the common standard metric to evaluate binary classi
Externí odkaz:
https://doaj.org/article/6cfe2c3eaf77447db26af73e140cc6fb
Autor:
Marco Chierici, Nicolae Puica, Matteo Pozzi, Antonello Capistrano, Marcello Dorian Donzella, Antonio Colangelo, Venet Osmani, Giuseppe Jurman
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 22, Iss S6, Pp 1-10 (2022)
Abstract Background The SI-CURA project (Soluzioni Innovative per la gestione del paziente e il follow up terapeutico della Colite UlceRosA) is an Italian initiative aimed at the development of artificial intelligence solutions to discriminate pathol
Externí odkaz:
https://doaj.org/article/e77ed6c287f94494b01e077870e22102
Publikováno v:
BioData Mining, Vol 15, Iss 1, Pp 1-23 (2022)
Abstract Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand which genes might be involved in
Externí odkaz:
https://doaj.org/article/1311db58c66748e99f8d48ec5518a469
Autor:
Simone Monaco, Nicole Bussola, Sara Buttò, Diego Sona, Flavio Giobergia, Giuseppe Jurman, Christodoulos Xinaris, Daniele Apiletti
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/ec36ce3fe58541368b9d312dbeec702a
Autor:
Alessia Marcolini, Nicole Bussola, Ernesto Arbitrio, Mohamed Amgad, Giuseppe Jurman, Cesare Furlanello
Publikováno v:
SoftwareX, Vol 20, Iss , Pp 101237- (2022)
Deep Learning (DL) is rapidly permeating the field of Digital Pathology with algorithms successfully applied to ease daily clinical practice and to discover novel associations. However, most DL workflows for Digital Pathology include custom code for
Externí odkaz:
https://doaj.org/article/a7c375ad79c4432f8105f183e7096f89
Autor:
Davide Chicco, Giuseppe Jurman
Publikováno v:
Frontiers in Bioinformatics, Vol 2 (2022)
Functional enrichment analysis or pathway enrichment analysis (PEA) is a bioinformatics technique which identifies the most over-represented biological pathways in a list of genes compared to those that would be associated with them by chance. These
Externí odkaz:
https://doaj.org/article/0292712e81a34c6d9f1fe4ec4c49aa4b