This chapter presents the applications of artificial intelligence (AI) and high-computing performance (HPC) in the health domain, illustrated by the description of five of the use cases that are developed in the DeepHealth project. In the context of the European Commission supporting the use of AI and HPC in the health sector, DeepHealth Project is helping health experts process large quantities of images, putting at their disposal DeepLearning and computer vision techniques, combined in the DeepHealth toolkit and HPC infrastructures. The DeepHealth toolkit is tested and validated through 15 use cases, each of them representing a biomedical application. The most promising use cases are described in the chapter, which concludes with the value proposition and the benefits that DeepHealth toolkit offers to future end users.
Applications of AI and HPC in the Health Domain
Franco Alberto Cardillo;
2021
Abstract
This chapter presents the applications of artificial intelligence (AI) and high-computing performance (HPC) in the health domain, illustrated by the description of five of the use cases that are developed in the DeepHealth project. In the context of the European Commission supporting the use of AI and HPC in the health sector, DeepHealth Project is helping health experts process large quantities of images, putting at their disposal DeepLearning and computer vision techniques, combined in the DeepHealth toolkit and HPC infrastructures. The DeepHealth toolkit is tested and validated through 15 use cases, each of them representing a biomedical application. The most promising use cases are described in the chapter, which concludes with the value proposition and the benefits that DeepHealth toolkit offers to future end users.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | en |
| dc.authority.people | Dana Oniga | en |
| dc.authority.people | Barbara Cantalupo | en |
| dc.authority.people | Daniele Perlo | en |
| dc.authority.people | Marco Grangetto | en |
| dc.authority.people | Federico Bolelli | en |
| dc.authority.people | Federico Pollastri | en |
| dc.authority.people | Michele Cancilla | en |
| dc.authority.people | Laura Canalini | en |
| dc.authority.people | Costantino Grana | en |
| dc.authority.people | Cristina Muñoz Alcalde | en |
| dc.authority.people | Franco Alberto Cardillo | en |
| dc.authority.people | Monica Florea | en |
| dc.authority.people | Enzo Tartaglione | en |
| dc.authority.people | Marco Aldinucci | en |
| dc.authority.project | Deep-Learning and HPC to Boost Biomedical Applications for Health | en |
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| dc.collection.name | 02.01 Contributo in volume (Capitolo o Saggio) | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
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| dc.date.accessioned | 2024/02/19 18:36:45 | - |
| dc.date.available | 2024/02/19 18:36:45 | - |
| dc.date.firstsubmission | 2024/10/06 19:18:26 | * |
| dc.date.issued | 2021 | - |
| dc.date.submission | 2024/10/06 19:18:26 | * |
| dc.description.abstracteng | This chapter presents the applications of artificial intelligence (AI) and high-computing performance (HPC) in the health domain, illustrated by the description of five of the use cases that are developed in the DeepHealth project. In the context of the European Commission supporting the use of AI and HPC in the health sector, DeepHealth Project is helping health experts process large quantities of images, putting at their disposal DeepLearning and computer vision techniques, combined in the DeepHealth toolkit and HPC infrastructures. The DeepHealth toolkit is tested and validated through 15 use cases, each of them representing a biomedical application. The most promising use cases are described in the chapter, which concludes with the value proposition and the benefits that DeepHealth toolkit offers to future end users. | - |
| dc.description.affiliations | SIMAVI, Romania Dipartimento di Informatica - Università degli Studi di Torino, Italia Dipartimento di Informatica - Università degli Studi di Torino, Italia Dipartimento di Informatica - Università degli Studi di Torino, Italia Dipartimento di Ingegneria "Enzo Ferrari" - Università di Modena e Reggio Emilia, Italia Dipartimento di Ingegneria "Enzo Ferrari" - Universita degli Studi di Modena e Reggio Emilia, Italia Dipartimento di Ingegneria "Enzo Ferrari" - Universita degli Studi di Modena e Reggio Emilia, Italia Dipartimento di Ingegneria "Enzo Ferrari" - Universita degli Studi di Modena e Reggio Emilia, Italia Dipartimento di Ingegneria "Enzo Ferrari" - Universita degli Studi di Modena e Reggio Emilia, Italia NTT DATA Europe & LATAM, Spagna Istituto di Linguistica Computazionale, CNR, Italia SIVECO, Romania Dipartimento di Informatica - Università degli Studi di Torino, Italia Dipartimento di Informatica - Università degli Studi di Torino, Italia | - |
| dc.description.allpeople | Oniga, Dana; Cantalupo, Barbara; Perlo, Daniele; Grangetto, Marco; Bolelli, Federico; Pollastri, Federico; Cancilla, Michele; Canalini, Laura; Grana, Costantino; Muñoz Alcalde, Cristina; Cardillo, FRANCO ALBERTO; Florea, Monica; Tartaglione, Enzo; Aldinucci, Marco | - |
| dc.description.allpeopleoriginal | Dana Oniga, Barbara Cantalupo, Daniele Perlo, Marco Grangetto, Federico Bolelli, Federico Pollastri, Michele Cancilla, Laura Canalini, Costantino Grana, Cristina Muñoz Alcalde, Franco Alberto Cardillo, Monica Florea, Enzo Tartaglione, Marco Aldinucci | en |
| dc.description.fulltext | restricted | en |
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| dc.identifier.doi | 10.1201/9781003176664-11 | en |
| dc.identifier.isbn | 9781003176664 | en |
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| dc.identifier.uri | https://hdl.handle.net/20.500.14243/448229 | - |
| dc.identifier.url | https://www.taylorfrancis.com/chapters/edit/10.1201/9781003176664-11/applications-ai-hpc-health-domain-dana-oniga-barbara-cantalupo-enzo-tartaglione-daniele-perlo-marco-grangetto-marco-aldinucci-federico-bolelli-federico-pollastri-michele-cancilla-laura-canalini-costantino-grana-cristina-muñoz-alcalde-franco-alberto-cardillo-monica-florea | en |
| dc.language.iso | eng | en |
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| dc.publisher.country | GBR | en |
| dc.publisher.name | CRC Press - Taylor & Francis Group | en |
| dc.publisher.place | London | en |
| dc.relation.allauthors | Olivier Terzo, Jan Martinovič | en |
| dc.relation.firstpage | 217 | en |
| dc.relation.ispartofbook | HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision | en |
| dc.relation.lastpage | 239 | en |
| dc.relation.numberofpages | 23 | en |
| dc.relation.projectAcronym | DeepHealth | en |
| dc.relation.projectAwardNumber | 825111 | en |
| dc.relation.projectAwardTitle | Deep-Learning and HPC to Boost Biomedical Applications for Health | en |
| dc.relation.projectFunderName | - | en |
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| dc.subject.keywordseng | artificial intelligence | - |
| dc.subject.keywordseng | high performance computing | - |
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| dc.title | Applications of AI and HPC in the Health Domain | en |
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| scopus.description.abstracteng | This chapter presents the applications of artificial intelligence (AI) and high-computing performance (HPC) in the health domain, illustrated by the description of five of the use cases that are developed in the DeepHealth project. In the context of the European Commission supporting the use of AI and HPC in the health sector, DeepHealth Project is helping health experts process large quantities of images, putting at their disposal DeepLearning and computer vision techniques, combined in the DeepHealth toolkit and HPC infrastructures. The DeepHealth toolkit is tested and validated through 15 use cases, each of them representing a biomedical application. The most promising use cases are described in the chapter, which concludes with the value proposition and the benefits that DeepHealth toolkit offers to future end users. | * |
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| scopus.title | Applications of AI and HPC in the Health Domain | * |
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