Conference Proceedings
A Medical Decision Support System for Explainable Multimodal Detection of Non Small Cell Lung Cancer Using Clinical and PET Data
EXPLAINABILITY 2024 : The First International Conference on Systems Explainability
Investigating the Agreement with Human Readers and Generalisation Capabilities of a Transfer Learning Approach for Predicting the Malignancy of Solitary Pulmonary Nodules in CT Screening
in 2024 15th International Conference on Information, Intelligence, Systems \& Applications (IISA), Chania Crete, Greece, 2024, pp. 1-6, doi: 10.1109/IISA62523.2024.10786628
Medical Decision Support System in Nuclear Medicine Diagnosis for Non-Small Cell Lung Cancer and Coronary Artery Disease: A First Stage Prototype
in 2024 15th International Conference on Information, Intelligence, Systems \& Applications (IISA), Chania Crete, Greece, 2024, pp. 1-8, doi: 10.1109/IISA62523.2024.10786612
Explainable prediction of coronary artery disease in nuclear medical imaging using deep learning
Accepted: EANM2022 Aim/Introduction: Coronary artery disease (CAD), also called ischemic heart disease, is the leading cause of death worldwide. Early CAD detection is unavoidably critical for the patient’s health and, more specifically, for the determination of an effective treatment. To enable reliable and trustworthy decisions, nuclear imaging specialists would require an autonomous diagnostic tool that
Deep learning for automatic diagnosis of coronary artery disease using SPECT MPI images
Accepted: EANM2022 Aim/Introduction: Coronary Artery Disease (CAD) exhibits the highest mortality rate among various heart diseases. The severity of CAD has enforced research to provide support from computer-aided systems of near-optimal accuracy in image classification and anomaly detection functionalities. Our research addresses the three-class image classification in CAD to detect normal state, ischemia or infarction,
Deep learning for automatic diagnosis of coronary artery disease using SPECT MPI images Read More »
