D
Dimitrios I. Fotiadis
Researcher at University of Ioannina
Publications - 767
Citations - 18727
Dimitrios I. Fotiadis is an academic researcher from University of Ioannina. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 60, co-authored 677 publications receiving 14779 citations. Previous affiliations of Dimitrios I. Fotiadis include University of Patras & Foundation for Research & Technology – Hellas.
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Journal ArticleDOI
Machine learning applications in cancer prognosis and prediction.
Konstantina Kourou,Themis P. Exarchos,Konstantinos P. Exarchos,Michalis V. Karamouzis,Dimitrios I. Fotiadis +4 more
TL;DR: Given the growing trend on the application of ML methods in cancer research, this work presents here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.
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Artificial neural networks for solving ordinary and partial differential equations
TL;DR: This article illustrates the method by solving a variety of model problems and presents comparisons with solutions obtained using the Galekrkin finite element method for several cases of partial differential equations.
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Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis
TL;DR: The suitability of the time-frequency ( t-f) analysis to classify EEG segments for epileptic seizures, and several methods for t- f analysis of EEGs are compared.
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Automatic seizure detection based on time-frequency analysis and artificial neural networks
TL;DR: A method of analysis of EEG signals, which is based on time-frequency analysis, which provides the final classification of the EEG segments concerning the existence of seizures or not.
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Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
TL;DR: In this paper, the authors present a method to solve initial and boundary value problems using artificial neural networks, where a trial solution of the differential equation is written as a sum of two parts, the first part satisfies the boundary (or initial) conditions and contains no adjustable parameters.