Search Results - "Apostolopoulos, Ioannis D."

Artificial Intelligence Algorithms for Epiretinal Membrane Detection, Segmentation and Postoperative BCVA Prediction: A Systematic Review and Meta-Analysis.

Authors: Maliagkani, Eirini Mitri, Petroula Mitsopoulou, Dimitra et al.

Source: Applied Sciences (2076-3417); Nov2025, Vol. 15 Issue 22, p12280, 29p

A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction Using Deep Learning.

Authors: Apostolopoulos, Ioannis D. Papandrianos, Nikolaοs Ι. Papageorgiou, Elpiniki I. et al.

Source: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 20, p11287, 26p

A machine learning approach for determining solitary pulmonary nodule malignancy in patients undergoing PET/CT examination.

Authors: Apostolopoulos, Ioannis D. Papathanasiou, Nikolaos D. Apostolopoulos, Dimitris J. et al.

Source: Multimedia Tools & Applications; Sep2025, Vol. 84 Issue 32, p39905-39924, 20p

Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights.

Authors: Feleki, Anna Apostolopoulos, Ioannis D. Moustakidis, Serafeim et al.

Source: Applied Sciences (2076-3417); Nov2023, Vol. 13 Issue 21, p11953, 21p

Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism.

Authors: Apostolopoulos, Dimitris J. Apostolopoulos, Ioannis D. Papathanasiou, Nikolaos D. et al.

Source: Algorithms. Sep2023, Vol. 16 Issue 9, p435. 16p.

Fuzzy Cognitive Maps: Their Role in Explainable Artificial Intelligence.

Authors: Apostolopoulos, Ioannis D. Groumpos, Peter P.

Source: Applied Sciences (2076-3417); Mar2023, Vol. 13 Issue 6, p3412, 16p

MedScanGAN: Synthetic PET & CT Scan Generation Using Conditional Generative Adversarial Networks for Medical AI Data Augmentation.

Authors: Samaras, Agorastos-Dimitrios Apostolopoulos, Ioannis D. Papandrianos, Nikolaos

Source: Bioengineering (Basel). Mar2026, Vol. 13 Issue 3, p281. 17p.

Explainable Machine Learning Prognosis of Coronary Artery Disease Using Lifestyle and Medical History Data.

Authors: Samaras, Agorastos-Dimitrios Apostolopoulos, Ioannis D. Papageorgiou, Elpiniki et al.

Source: Applied Sciences (2076-3417); Jun2026, Vol. 16 Issue 11, p5444, 17p

Clinician-Centered Evaluation Framework for Explainable AI Heatmaps in OCT-Based Retinal Disease Classification.

Authors: Maliagkani, Eirini Georgalas, Ilias Datseris, Ioannis et al.

Source: Journal of Imaging; May2026, Vol. 12 Issue 5, p211, 25p

An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM.

Authors: Papandrianos, Nikolaos I. Feleki, Anna Moustakidis, Serafeim et al.

Source: Applied Sciences (2076-3417); Aug2022, Vol. 12 Issue 15, p7592-7592, 21p

Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease.

Authors: Apostolopoulos, Ioannis D. Papathanasiou, Nikolaοs D. Papandrianos, Nikolaos et al.

Source: Applied Sciences (2076-3417); Aug2023, Vol. 13 Issue 15, p8839, 21p

Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models.

Authors: Samaras, Agorastos-Dimitrios Moustakidis, Serafeim Apostolopoulos, Ioannis D. et al.

Source: Applied Sciences (2076-3417); Jul2023, Vol. 13 Issue 14, p8120, 14p

Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning.

Authors: Apostolopoulos, Ioannis D. Androulakis, Silas Kalkavouras, Panayiotis et al.

Source: Sensors (14248220). Jul2024, Vol. 24 Issue 13, p4110. 27p.

Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review.

Authors: Apostolopoulos, Ioannis D. Papathanasiou, Nikolaos D. Apostolopoulos, Dimitris J. et al.

Source: European Journal of Nuclear Medicine & Molecular Imaging. Sep2022, Vol. 49 Issue 11, p3717-3739. 23p. 5 Color Photographs, 2 Black and White Photographs, 3 Diagrams, 6 Charts, 1 Graph.

Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies.

Authors: Apostolopoulos, Ioannis D. Papandrianos, Nikolaos I. Feleki, Anna et al.

Source: EJNMMI Physics. 1/27/2023, Vol. 10 Issue 1, p1-43. 43p.

Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis.

Authors: Apostolopoulos, Ioannis D. Papandrianos, Nikolaos I. Apostolopoulos, Dimitrios J. et al.

Source: Bioengineering (Basel). Oct2024, Vol. 11 Issue 10, p957. 16p.

Deep Learning Methods to Reveal Important X-ray Features in COVID-19 Detection: Investigation of Explainability and Feature Reproducibility.

Authors: Apostolopoulos, Ioannis D. Apostolopoulos, Dimitris J. Papathanasiou, Nikolaos D.

Source: Reports (MDPI AG). Jun2022, Vol. 5 Issue 2, pN.PAG-N.PAG. 18p.

Fuzzy Cognitive Map Applications in Medicine over the Last Two Decades: A Review Study.

Authors: Apostolopoulos, Ioannis D. Papandrianos, Nikolaos I. Papathanasiou, Nikolaos D. et al.

Source: Bioengineering (Basel). Feb2024, Vol. 11 Issue 2, p139. 26p.

A General Machine Learning Model for Assessing Fruit Quality Using Deep Image Features.

Authors: Apostolopoulos, Ioannis D. Tzani, Mpesi Aznaouridis, Sokratis I.

Source: AI. Dec2023, Vol. 4 Issue 4, p812-830. 19p.

A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination.

Authors: Apostolopoulos, Ioannis D. Papathanasiou, Nikolaos D. Apostolopoulos, Dimitris J. et al.

Source: Big Data & Cognitive Computing; Aug2024, Vol. 8 Issue 8, p85, 22p