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Dimitrios I. Fotiadis

Dimitrios I. Fotiadis

Award Badge
Computer Science
Greece
2026

D-Index & Metrics

Computer Science

D-Index
71
Citations
23657
World Ranking
1760
National Ranking
4

Research.com Recognitions

  • 2026 - Research.com Computer Science in Greece Leader Award
  • 2025 - Research.com Computer Science in Greece Leader Award
  • 2023 - Research.com Computer Science in Greece Leader Award
  • 2022 - Research.com Computer Science in Greece Leader Award
  • 2019 - IEEE Fellow For contributions to modelling and machine learning in biomedical data processing

Overview

Dimitrios I. Fotiadis is affiliated with the University of Ioannina in Greece and specializes primarily in the field of Medicine. Their research spans several subfields, including Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Surgery, and Pulmonary and Respiratory Medicine.

The main topics of their research work cover a wide spectrum of medical and technological areas:

  • Coronary Interventions and Diagnostics
  • Cerebrovascular and Carotid Artery Diseases
  • Radiomics and Machine Learning in Medical Imaging
  • Parkinson's Disease Mechanisms and Treatments
  • Cardiac Imaging and Diagnostics
  • Artificial Intelligence in Healthcare
  • Cardiovascular Health and Disease Prevention

Among recent publications, notable papers include:

  • Deep learning for diabetic retinopathy detection and classification based on fundus images: A review, 2021, Computers in Biology and Medicine
  • Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis, 2021, Computational and Structural Biotechnology Journal
  • The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson's Patients, 2021, Sensors
  • Primary Sjögren's Syndrome of Early and Late Onset: Distinct Clinical Phenotypes and Lymphoma Development, 2020, Frontiers in Immunology
  • A prospective multicenter study assessing humoral immunogenicity and safety of the mRNA SARS-CoV-2 vaccines in Greek patients with systemic autoimmune and autoinflammatory rheumatic diseases, 2021, Journal of Autoimmunity

Frequent co-authors working alongside Dimitrios I. Fotiadis include:

  • Nikolaos S. Tachos
  • Vasileios C. Pezoulas
  • Manolis Tsiknakis
  • Kostas Marias
  • Antonis I. Sakellarios

The scientist regularly publishes in notable venues such as:

  • 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
  • Sensors
  • Diagnostics
  • 2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Dimitrios I. Fotiadis has also contributed to book literature with the publication titled Digital Health Technology for Better Aging in 2021 under Springer International Publishing.

Recognition of their work includes the IEEE Fellow award in 2019, granted for contributions to modeling and machine learning in biomedical data processing.

Best Publications

  • Machine learning applications in cancer prognosis and prediction.

    Konstantina Kourou;Themis P. Exarchos;Konstantinos P. Exarchos;Michalis V. Karamouzis

  • Artificial neural networks for solving ordinary and partial differential equations

    I.E. Lagaris;A. Likas;D.I. Fotiadis

  • Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis

    A.T. Tzallas;M.G. Tsipouras;D.I. Fotiadis

  • A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

    Κostas Μ. Tsiouris;Vasileios C. Pezoulas;Michalis Zervakis;Spiros Konitsiotis

  • Automatic seizure detection based on time-frequency analysis and artificial neural networks

    A. T. Tzallas;M. G. Tsipouras;D. I. Fotiadis

  • Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach

    C.D. Katsis;N. Katertsidis;G. Ganiatsas;D.I. Fotiadis

  • Hydrodynamics of magnetic drug targeting.

    P.A. Voltairas;D.I. Fotiadis;L.K. Michalis

  • An arrhythmia classification system based on the RR-interval signal

    M. G. Tsipouras;D. I. Fotiadis;D. Sideris

  • Review of eye tracking metrics involved in emotional and cognitive processes.

    Vasileios Skaramagkas;Giorgos Giannakakis;Emmanouil Ktistakis;Dimitris Manousos

  • Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

    Nikos Tsiknakis;Dimitris Theodoropoulos;Georgios C. Manikis;Emmanouil Ktistakis

  • Assessment of Tremor Activity in the Parkinson’s Disease Using a Set of Wearable Sensors

    G. Rigas;A. T. Tzallas;M. G. Tsipouras;P. Bougia

  • Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling

    M.G. Tsipouras;T.P. Exarchos;D.I. Fotiadis;A.P. Kotsia

  • Heart Failure: Diagnosis, Severity Estimation and Prediction of Adverse Events Through Machine Learning Techniques.

    Evanthia E. Tripoliti;Theofilos G. Papadopoulos;Georgia S. Karanasiou;Katerina K. Naka

  • Automatic detection of freezing of gait events in patients with Parkinson's disease

    Evanthia E. Tripoliti;Alexandros T. Tzallas;Markos G. Tsipouras;George Rigas

  • Multivariate Prediction of Subcutaneous Glucose Concentration in Type 1 Diabetes Patients Based on Support Vector Regression

    E. I. Georga;V. C. Protopappas;Diego Ardigo;M. Marina

  • Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines

    A. Papadopoulos;D. I. Fotiadis;A. Likas

  • PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease

    Alexandros T. Tzallas;Markos G. Tsipouras;Georgios Rigas;Dimitrios G. Tsalikakis

  • Artificial neural network methods in quantum mechanics

    I.E. Lagaris;A. Likas;D.I. Fotiadis

  • Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques

    A. Papadopoulos;D. I. Fotiadis;L. Costaridou

  • A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree

    Themis P. Exarchos;Markos G. Tsipouras;Costas P. Exarchos;Costas Papaloukas

  • An automatic microcalcification detection system based on a hybrid neural network classifier

    A. Papadopoulos;D. I. Fotiadis;A. Likas

Frequent Co-Authors

Markos G. Tsipouras
Markos G. Tsipouras University of Western Macedonia
Aristidis Likas
Aristidis Likas University of Ioannina
Konstantina S. Nikita
Konstantina S. Nikita National Technical University of Athens
Manolis Tsiknakis
Manolis Tsiknakis Foundation for Research and Technology Hellas

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