Zobrazeno 1 - 10
of 214
pro vyhledávání: '"D, Magoulas"'
Autor:
Nitsa J. Herzog, George D. Magoulas
Publikováno v:
Sensors, Vol 21, Iss 3, p 778 (2021)
Early identification of degenerative processes in the human brain is considered essential for providing proper care and treatment. This may involve detecting structural and functional cerebral changes such as changes in the degree of asymmetry betwee
Externí odkaz:
https://doaj.org/article/bcbc9057b96a49b898862a82557c6cec
Autor:
Nitsa J Herzog, George D Magoulas
Publikováno v:
International journal of neural systems. 32(12)
Computer-aided diagnosis of health problems and pathological conditions has become a substantial part of medical, biomedical, and computer science research. This paper focuses on the diagnosis of early and progressive dementia, building on the potent
Autor:
George Kyriakopoulos, Seferina Mavroudi, Constantinos Stathopoulos, Denis Drainas, Dimitrios G. Anastasakis, Christos K. Kontos, Ilias Skeparnias, Andreas Scorilas, George D. Magoulas, Aigli Korfiati, Katerina Grafanaki, Dionissios Papaioannou, Konstantinos Theofilatos
Publikováno v:
The Pharmacogenomics Journal. 21:638-648
Retinoids are widely used in diseases spanning from dermatological lesions to cancer, but exhibit severe adverse effects. A novel all-trans-Retinoic Acid (atRA)-spermine conjugate (termed RASP) has shown previously optimal in vitro and in vivo anti-i
Publikováno v:
Artificial Life. 26:217-241
Children's acquisition of the English past tense has been widely studied as a testing ground for theories of language development, mostly because it comprises a set of quasi-regular mappings. English verbs are of two types: regular verbs, which form
Publikováno v:
Engineering Applications of Neural Networks ISBN: 9783031082221
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f25384d28e9819e6daadaae02c7c010b
https://doi.org/10.1007/978-3-031-08223-8_34
https://doi.org/10.1007/978-3-031-08223-8_34
Autor:
Nitsa J. Herzog, George D. Magoulas
Publikováno v:
Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783031208362
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80b7055f415e9e879b116a0d37bd0bc7
https://doi.org/10.1007/978-3-031-20837-9_5
https://doi.org/10.1007/978-3-031-20837-9_5
Autor:
Tomasz D. Sikora, George D. Magoulas
Publikováno v:
Enterprise Information Systems. 15:133-173
Currently, data centres employ much more computational power, machines and energy than it is really needed to provide the required level of service and ensure customer satisfaction. This is a resul...
Publikováno v:
Proceedings of the International Neural Networks Society ISBN: 9783030805678
EANN
EANN
Developing digital biomarkers that would enable reliable detection of autism–ASD early in life is challenging because of the variability in the presentation of the autistic disorder and the need for simple measurements that could be implemented rou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8a9a999e956eaf7c976fd08d7f7a867
https://doi.org/10.1007/978-3-030-80568-5_6
https://doi.org/10.1007/978-3-030-80568-5_6
Autor:
Nitsa J. Herzog, George D. Magoulas
Publikováno v:
Proceedings of the International Neural Networks Society ISBN: 9783030805678
EANN
EANN
Advances in neural networks and deep learning have opened a new era in medical imaging technology, health care data analysis and clinical diagnosis. This paper focuses on the classification of MRI for diagnosis of early and progressive dementia using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::221d0d08602b7a541d666262cfb863f8
https://doi.org/10.1007/978-3-030-80568-5_5
https://doi.org/10.1007/978-3-030-80568-5_5
Publikováno v:
Proceedings of the International Neural Networks Society ISBN: 9783030805678
EANN
22nd International Conference on Engineering Applications of Neural Networks
EANN
22nd International Conference on Engineering Applications of Neural Networks
We introduce an algorithm for one-class classification based on binary classification of the target class against synthetic samples. We use a process inspired by Generative Adversarial Networks (GANs) in order to both acquire synthetic samples and to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::053815b64670600f6c2649453dd1e084
https://doi.org/10.1007/978-3-030-80568-5_2
https://doi.org/10.1007/978-3-030-80568-5_2