Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Agapi Aggelopoulou"'
Autor:
Vitaliano Quaranta, Christos Kyriakopoulos, Angelos Liontos, Fotios Barkas, Christos Chronis, Dimitrios Biros, Lazaros Athanasiou, Orestis Milionis, Stavros Tsourlos, Cornelia Veliani, Alexandros Papathanasiou, Valentini Samanidou, Agapi Aggelopoulou, Vanesa Bellou, Christiana Pappa, Nikolaos-Gavriil Kolios, Sempastien Filippas-Ntekouan, Giovanna Carpagnano, Silvano Dragonieri, Eirini Christaki, Athanasios Konstantinidis, Haralampos Milionis, Konstantinos Kostikas
Publikováno v:
Pneumon. 35:1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae54e33ab8d426325c9150dc08636ff0
https://doi.org/10.18332/pne/146178
https://doi.org/10.18332/pne/146178
Autor:
Konstantinos Exarchos, Agapi Aggelopoulou, Aikaterini Oikonomou, Theodora Biniskou, Vasiliki Beli, Eirini Antoniadou, Konstantinos Kostikas
Publikováno v:
IEEE journal of biomedical and health informatics. 26(5)
Artificial Intelligence (AI) has proven to be an invaluable asset in the healthcare domain, where massive amounts of data are produced. Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous chronic condition with multiscale manifestations a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1ae29c1327bbdbb969ef16095dd236d
https://pubmed.ncbi.nlm.nih.gov/34914601
https://pubmed.ncbi.nlm.nih.gov/34914601
Autor:
Dimitrios Potonos, Agapi Aggelopoulou, Konstantinos P. Exarchos, Konstantinos Kostikas, Agni Sioutkou
Publikováno v:
m-Health/e-health.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e10adaaf24494fb5f4ba53b65d1ebf5a
https://doi.org/10.1183/13993003.congress-2021.pa3442
https://doi.org/10.1183/13993003.congress-2021.pa3442
Autor:
Konstantinos Bartziokas, Christos F. Tagkas, Agapi Aggelopoulou, Konstantinos Kostikas, Olga Toli, Konstantinos P. Exarchos, Vasileios Drouvis, Elpida Tsina
Publikováno v:
Pulmonary embolism.
Introduction: Pulmonary embolism (PE) is a common life-threatening condition. Underdiagnosis and delays in the diagnosis are common, mainly due to unspecific clinical presentations. Aim: We used clinical parameters to train a Machine Learning algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74a142910f0501839939eee7092b4ac9
https://doi.org/10.1183/13993003.congress-2020.4972
https://doi.org/10.1183/13993003.congress-2020.4972