3D MRU-Net: A novel mobile residual U-Net deep learning model for spine segmentation using computed tomography images. - Muhammad Usman Saeed; Bin Wang 017; Jinfang Sheng; Ghulam Ali; Aqsa Dastgir (Biomed. Signal Process. Control., 2023)

MSFF: An automated multi-scale feature fusion deep learning model for spine fracture segmentation using MRI. - Muhammad Usman Saeed; Bin Wang 017; Jinfang Sheng; Hussain Mobarak Albarakati; Aqsa Dastgir (Biomed. Signal Process. Control., 2024)

Enhancing anemia detection through multimodal data fusion: a non-invasive approach using EHRs and conjunctiva images. - Muhammad Ramzan; Muhammad Usman Saeed; Ghulam Ali (Discov. Artif. Intell., 2024)

Revolutionizing anemia detection: integrative machine learning models and advanced attention mechanisms. - Muhammad Ramzan; Jinfang Sheng; Muhammad Usman Saeed; Bin Wang 017; Faisal Z. Duraihem (Vis. Comput. Ind. Biomed. Art, 2024)

3D MFA: An automated 3D Multi-Feature Attention based approach for spine segmentation using a multi-stage network pruning. - Muhammad Usman Saeed; Wang Bin; Jinfang Sheng; Salman Saleem (Comput. Biol. Medicine, 2025)

MAFMv3: An automated Multi-Scale Attention-Based Feature Fusion MobileNetv3 for spine lesion classification. - Aqsa Dastgir; Bin Wang 017; Muhammad Usman Saeed; Jinfang Sheng; Salman Saleem (Image Vis. Comput., 2025)

Empowering cardiovascular diagnostics with SET-MobileNet: A lightweight and accurate deep learning based classification approach. - Zunair Safdar; Jinfang Sheng; Muhammad Usman Saeed; Muhammad Ramzan; A. Al-Zubaidi (Image Vis. Comput., 2025)