PhD student Anna Feleki member of the EMERALD team presented the publication titled “Multimodal Diagnosis using Deep Fuzzy Cognitive Map with Extreme Learning Machine Integrated into a Medical Decision Support System for Coronary Artery Disease and Non-Small Cell Lung Cancer Detection” at the 28th Pan-Hellenic Conference on Progress in Computing Informatics with International Participation, held from December 13th-15th, 2024, in Athens, Greece. The paper outlines the enhancement of DeepFCM with the Extreme Learning Machine (ELM), as a learning technique, to improve the early diagnosis of CAD and NSCLC. The team’s approach integrates clinical and imaging data and emphasizes explainability in medical decision-making, providing valuable insights into the diagnosis of both diseases. The application of Natural Language Generation enables human-understandable explanations of the decision-making process, showcasing the practical impact of AI in healthcare.
