Dr. Maytham N Meqdad, Rapporteur of the Intelligent Medical Systems Department, Publishes Research in the International Journal Intelligence-Based Medicine Dr. Maytham Nabil Meqdad, Rapporteur of the Intelligent Medical Systems Department at the College of Science, Al-Mustaqbal University, has published a scientific research paper in the international journal Intelligence-Based Medicine, published by Elsevier, in Volume 16 (2026), entitled: “Wolff–Parkinson–White Syndrome Screening from ECG via TinyFLFormer: A Tensor-Decomposed Dual-Stream Transformer with Diffusion-Guided Knowledge Distillation.” The study presents an intelligent framework for detecting Wolff–Parkinson–White (WPW) syndrome through the analysis of 12-lead electrocardiogram (ECG) signals, employing artificial intelligence, deep learning, and Transformer-based technologies. The research aims to support the automated detection of WPW syndrome and improve the efficiency of models used for cardiac signal analysis. The study utilized data from the PTB-XL database, analyzing 21,799 ECG recordings, including 1,077 recordings positive for WPW syndrome. The researchers developed a compact intelligent model, TinyFLFormer, designed to achieve computational efficiency while retaining a significant proportion of the diagnostic performance of a high-capacity teacher model. The results demonstrated that the proposed model achieved an accuracy of 86.30%, sensitivity of 83.54%, and a Matthews Correlation Coefficient (MCC) of 73.04%, while utilizing only 0.23 million parameters and 177.94 MFLOPs. The model also achieved a substantial reduction in model size and faster inference compared with the reference model, supporting its potential deployment in resource-constrained medical devices, portable ECG systems, and wearable healthcare technologies. The publication of this research in Intelligence-Based Medicine reflects the Intelligent Medical Systems Department’s continued interest in applying artificial intelligence and deep learning techniques to develop smart medical solutions that support early diagnosis, enhance the efficiency of biomedical signal analysis, and strengthen the University’s research presence in the field of medical artificial intelligence. Source: Intelligence-Based Medicine – Elsevier, Volume 16, Article 100489, November 2026. Al-Mustaqbal University – Iraq’s No. 1 University