TY - JOUR
T1 - HPC+ in the medical field
T2 - Overview and current examples
AU - Koch, Miriam
AU - Arlandini, Claudio
AU - Antonopoulos, Gregory
AU - Baretta, Alessia
AU - Beaujean, Pierre
AU - Bex, Geert Jan
AU - Biancolini, Marco Evangelos
AU - Celi, Simona
AU - Costa, Emiliano
AU - Drescher, Lukas
AU - Eleftheriadis, Vasileios
AU - Fadel, Nur A.
AU - Fink, Andreas
AU - Galbiati, Federica
AU - Hatzakis, Ilias
AU - Hompis, Georgios
AU - Lewandowski, Natalie
AU - Memmolo, Antonio
AU - Mensch, Carl
AU - Obrist, Dominik
AU - Paneta, Valentina
AU - Papadimitroulas, Panagiotis
AU - Petropoulos, Konstantinos
AU - Porziani, Stefano
AU - Savvidis, Georgios
AU - Sethia, Khyati
AU - Strakos, Petr
AU - Svobodova, Petra
AU - Vignali, Emanuele
N1 - Publisher Copyright:
© 2023 - The authors. Published by IOS Press.
PY - 2023
Y1 - 2023
N2 - Background: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together 'HPC+'). Objective: This overview article aims to show state-of-the-art examples of studies supported by the National Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications. Method: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures. Results: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research. Conclusion: HPC+ support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research.
AB - Background: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together 'HPC+'). Objective: This overview article aims to show state-of-the-art examples of studies supported by the National Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications. Method: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures. Results: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research. Conclusion: HPC+ support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research.
KW - AI (artificial intelligence)
KW - computational modeling
KW - Computer simulation
KW - data analysis
KW - diagnosis
KW - medicine
KW - therapeutics
UR - http://www.scopus.com/inward/record.url?scp=85152477692&partnerID=8YFLogxK
U2 - 10.3233/THC-229015
DO - 10.3233/THC-229015
M3 - Article
C2 - 36641699
AN - SCOPUS:85152477692
SN - 0928-7329
VL - 31
SP - 1509
EP - 1523
JO - Technology and Health Care
JF - Technology and Health Care
IS - 4
ER -