بەشی زانستی کۆمپیوتەر چالاکییەکی خێرخوازی ڕێکدەخات بۆ پاڵپشتیکردنی خێزانە پێویستەکان
Assistant Professor Dr. Lway Faisal from the Computer Science Department at Cihan University Sulaimaniya has made significant contributions to medical AI research, publishing in two high-impact Q1 Scopus-indexed journals: Scientific Reports (IF 3.8) and Computers in Biology and Medicine (IF 7).
His first study, “A Privacy-Preserving Dependable Deep Federated Learning Model for Identifying New Infections from Genome Sequences,” addresses the security challenges in traditional molecular-based identification (TMID) techniques. The research introduces a privacy-preserving deep federated learning (DFL) model that effectively selects features for identifying new infections while safeguarding sensitive medical data. Conducted in collaboration with institutions from Bangladesh, Saudi Arabia, Australia, and Canada, this study highlights the power of global partnerships in AI-driven healthcare solutions.
Article Link: https://www.nature.com/articles/s41598-025-89612-x
His second paper, “StackTHP: A Stacking Ensemble Model for Accurate Prediction of Tumor-Homing Peptides in Cancer Therapy,” presents an innovative hybrid approach integrating AAC and PAAC feature extractors to enhance tumor-homing peptide (THP) prediction. The model achieves remarkable accuracy (91.92%), with an MCC of 0.8415 and an AUC of 0.977, outperforming existing models while optimizing computational efficiency.
Article Link: https://www.sciencedirect.com/science/article/pii/S0010482525003099
These studies exemplify Cihan University Sulaimaniya’s dedication to impactful AI research in healthcare, driving innovation in infection detection and cancer therapy.
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