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Citations (13)
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Khalidou Abdoulaye Barry, Youness Manzali, Rachid Flouchi, Youssef Balouki, Khadija Chelhi & Mohamed Elfar. (2023) Exploring the use of association rules in random forest for predicting heart disease. Computer Methods in Biomechanics and Biomedical Engineering 0:0, pages 1-9.
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S. Aldo Lechuga Ensastiga, Juvenal Rodríguez-Reséndiz & Adyr A. Estévez-Bén. (2022) Speed controller-based fuzzy logic for a biosignal-feedbacked cycloergometer. Computer Methods in Biomechanics and Biomedical Engineering 25:7, pages 750-763.
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Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos & Nikolaos Papandrianos. (2023) Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights. Applied Sciences 13:21, pages 11953.
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Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou & Nikolaos Papandrianos. (2023) Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models. Applied Sciences 13:14, pages 8120.
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Rajeshwari Maramgere Ramaiah & Kavitha Kuntaegowdanalli Srikantegowda. (2023) CORONARY HEART DISEASE CLASSIFICATION USING IMPROVED PENGUIN EMPEROR OPTIMIZATION-BASED LONG SHORT TERM MEMORY NETWORK. IIUM Engineering Journal 24:2, pages 67-85.
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Okure Obot, Anietie John, Iberedem Udo, Kingsley Attai, Ekemini Johnson, Samuel Udoh, Chukwudi Nwokoro, Christie Akwaowo, Emem Dan, Uduak Umoh & Faith-Michael Uzoka. (2023) Modelling Differential Diagnosis of Febrile Diseases with Fuzzy Cognitive Map. Tropical Medicine and Infectious Disease 8:7, pages 352.
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Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Nikolaos Papandrianos & Elpiniki Papageorgiou. (2023) Classification models for assessing coronary artery disease instances using clinical and biometric data: an explainable man-in-the-loop approach. Scientific Reports 13:1.
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Ioannis D. Apostolopoulos & Peter P. Groumpos. (2023) Fuzzy Cognitive Maps: Their Role in Explainable Artificial Intelligence. Applied Sciences 13:6, pages 3412.
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Anna Feleki, Ioannis D. Apostolopoulos, Konstantinos Papageorgiou, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos & Nikolaos I. Papandrianos. 2023. Fuzzy Logic and Technology, and Aggregation Operators. Fuzzy Logic and Technology, and Aggregation Operators
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Ioannis D. Apostolopoulos, Ifigeneia Athanasoula, Mpesi Tzani & Peter P. Groumpos. (2022) An Explainable Deep Learning Framework for Detecting and Localising Smoke and Fire Incidents: Evaluation of Grad-CAM++ and LIME. Machine Learning and Knowledge Extraction 4:4, pages 1124-1135.
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Ioannis D. Apostolopoulos & Besiana A. Tzani. (2022) Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic. Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic.
Peter P. Groumpos & Ioannis D. Apostolopoulos. (2021) Modeling the spread of dangerous pandemics with the utilization of a hybrid-statistical–Advanced-Fuzzy-Cognitive-Map algorithm: the example of COVID-19. Research on Biomedical Engineering 37:4, pages 749-764.
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Ioannis D Apostolopoulos, Peter P Groumpos & Dimitris J Apostolopoulos. (2021) Advanced fuzzy cognitive maps: state-space and rule-based methodology for coronary artery disease detection. Biomedical Physics & Engineering Express 7:4, pages 045007.
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