N
Nikolaos Giannakeas
Researcher at University of Ioannina
Publications - 108
Citations - 883
Nikolaos Giannakeas is an academic researcher from University of Ioannina. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 13, co-authored 70 publications receiving 465 citations. Previous affiliations of Nikolaos Giannakeas include RMIT University & American Hotel & Lodging Educational Institute.
Papers
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Journal ArticleDOI
High-Throughput, Machine Learning-Based Quantification of Steatosis, Inflammation, Ballooning, and Fibrosis in Biopsies From Patients With Nonalcoholic Fatty Liver Disease.
Roberta Forlano,Benjamin H. Mullish,Nikolaos Giannakeas,James Maurice,N. Angkathunyakul,J. Lloyd,Alexandros T. Tzallas,Markos G. Tsipouras,Michael Yee,Mark Thursz,Robert D. Goldin,Pinelopi Manousou +11 more
TL;DR: In this paper, the authors used machine learning to develop fully automated software for quantification of steatosis, inflammation, ballooning, and fibrosis in biopsy specimens from patients with NAFLD and validated the technology in a separate group of patients.
Journal ArticleDOI
A robust methodology for classification of epileptic seizures in EEG signals
Katerina D. Tzimourta,Alexandros T. Tzallas,Nikolaos Giannakeas,Loukas G. Astrakas,Dimitrios G. Tsalikakis,Pantelis Angelidis,Markos G. Tsipouras,Markos G. Tsipouras +7 more
TL;DR: A multicenter methodology for automated seizure detection based on Discrete Wavelet Transform (DWT) is presented, reaching accuracy above 95% and confirming the robustness of the methodology.
Book ChapterDOI
Epileptic Seizures Classification Based on Long-Term EEG Signal Wavelet Analysis
Katerina D. Tzimourta,Alexandros T. Tzallas,Nikolaos Giannakeas,Loukas G. Astrakas,Dimitrios G. Tsalikakis,Markos G. Tsipouras +5 more
TL;DR: A methodology for automated seizure detection based on Discrete Wavelet Transform (DWT) is presented, using intracranial ictal recordings acquired from the database of University Hospital of Freiburg to train a Support Vector Machines (SVM) classifier.
Journal ArticleDOI
Derivation and validation of a cardiovascular risk score for prediction of major acute cardiovascular events in non-alcoholic fatty liver disease; the importance of an elevated mean platelet volume
Robin Daniel Abeles,Benjamin H. Mullish,Roberta Forlano,Torben Kimhofer,Maciej Adler,Alexandros T. Tzallas,Nikolaos Giannakeas,Michael Yee,Jamil Mayet,Robert D. Goldin,Mark Thursz,Pinelopi Manousou +11 more
TL;DR: Atherosclerotic cardiovascular disease is a key cause of morbidity in non‐alcoholic fatty liver disease (NAFLD) but appropriate means to predict major acute cardiovascular events (MACE) are lacking.
Journal ArticleDOI
EEG-Based Automatic Sleep Stage Classification
Katerina D. Tzimourta,Athanasios Tsilimbaris,Athanasios Tsilimbaris,Katerina Tzioukalia,Alexandros T. Tzallas,Markos G. Tsipouras,Loukas G. Astrakas,Nikolaos Giannakeas +7 more
TL;DR: A methodology for sleep staging using solely Electroencephalographic (EEG) signals from PSG recordings is presented, aiming to automatically identify the five sleep stages.