Publications

1. [1]
   Abdo, H.A., Abdu, A., Al-Antari, M.A., Manza, R.R., Talo, M., Gu, Y.H. and Bawiskar, S., 2024. End-to-End Deep Learning Framework for Arabic Handwritten Legal Amount Recognition and Digital Courtesy Conversion. Mathematics (2227-7390), 12(14). [link]

1. [2]
   Agbesi, Victor Kwaku, Wenyu Chen, Sophyani Banaamwini Yussif, Chiagoziem C. Ukwuoma, Yeong Hyeon Gu, and Mugahed A. Al-antari. "MuTCELM: An optimal multi-TextCNN-based ensemble learning for text classification." Heliyon 10, no. 19 (2024). [link]

1. [3]
   Mateen, Muhammad, Shaukat Hayat, Fizzah Arshad, Yeong-Hyeon Gu, and Mugahed A. Al-antari. "Hybrid Deep Learning Framework for Melanoma Diagnosis Using Dermoscopic Medical Images." Diagnostics 14, no. 19 (2024): 2242. [link]

1. [4]
   Al-Tam, R.M., Al-Hejri, A.M., Alshamrani, S.S., Al-antari, M.A. and Narangale, S.M., 2024. Multimodal breast cancer hybrid explainable computer-aided diagnosis using medical mammograms and ultrasound Images. Biocybernetics and Biomedical Engineering, 44(3), pp.731-758. [link]

1. [5]
   Ozkan, D., Katar, O., Ak, M., Al-antari, M.A., Ak, N.Y., Yildirim, O., Mir, H.S., Tan, R.S. and Acharya, U.R., 2024. Deep Learning Techniques for Automated Dementia Diagnosis Using Neuroimaging Modalities: A Systematic Review (2012-2023). IEEE Access. [link]

1. [6]
   Tohye, T.G., Qin, Z., Al-antari, M.A., Ukwuoma, C.C., Lonseko, Z.M. and Gu, Y.H., 2024. CA-ViT: Contour-Guided and Augmented Vision Transformers to Enhance Glaucoma Classification Using Fundus Images. Bioengineering, 11(9), p.887. [link]

1. [7]
   Farea, E., Saleh, R.A., AbuAlkebash, H., Farea, A.A. and Al-antari, M.A., 2024. A hybrid deep learning skin cancer prediction framework. Engineering Science and Technology, an International Journal, 57, p.101818. [link]

1. [8]
   Khan, H.U., Ali, Y., Khan, F. and Al-Antari, M.A., 2024. A comprehensive study on unraveling the advances of immersive technologies (VR/AR/MR/XR) in the healthcare sector during the COVID-19: Challenges and solutions. Heliyon, 10(15). [link]

1. [9]
   Al-antari, M.A., 2024. Artificial Intelligence Advances for Medical Computer-Aided Diagnosis. [link]

1. [10]
   Abdo, H.A., Abdu, A., Al-Antari, M.A., Manza, R.R., Talo, M., Gu, Y.H. and Bawiskar, S., 2024. End-to-End Deep Learning Framework for Arabic Handwritten Legal Amount Recognition and Digital Courtesy Conversion. Mathematics (2227-7390), 12(14). [link]

1. [11]
   Malik, I., Yasmin, M., Iqbal, A., Raza, M., Chun, C.J. and Al-antari, M.A., 2024. A novel framework integrating ensemble transfer learning and Ant Colony Optimization for Knee Osteoarthritis severity classification. Multimedia Tools and Applications, pp.1-32. [link]

1. [12]
   Ejiyi, C.J., Qin, Z., Ukwuoma, C., Agbesi, V.K., Oluwasanmi, A., Al-antari, M.A. and Bamisile, O., 2024. A unified 2D medical image segmentation network (SegmentNet) through distance-awareness and local feature extraction. Biocybernetics and Biomedical Engineering, 44(3), pp.431-449. [link]

1. [13]
   Al-antari, M.A., 2024. Advancements in Artificial Intelligence for Medical Computer-Aided Diagnosis. Diagnostics, 14(12), p.1265. [link]

1. [14]
   Atandoh, P., Zhang, F., Al-Antari, M.A., Addo, D. and Gu, Y.H., 2024. Scalable deep learning framework for sentiment analysis prediction for online movie reviews. Heliyon, 10(10). [link]

1. [15]
   Biroš, M., Kvak, D., Dandár, J., Hrubý, R., Janů, E., Atakhanova, A. and Al-Antari, M.A., 2024. Enhancing Accuracy in Breast Density Assessment Using Deep Learning: A Multicentric, Multi-Reader Study. Diagnostics, 14(11), p.1117. [link]

1. [16]
   Al-Masni, M.A., Marzban, E.N., Al-Shamiri, A.K., Al-Antari, M.A., Alabdulhafith, M.I., Mahmoud, N.F., Abdel Samee, N. and Kadah, Y.M., 2024. Gait Impairment Analysis Using Silhouette Sinogram Signals and Assisted Knowledge Learning. Bioengineering, 11(5), p.477. [link]

1. [17]
   Muaad, A.Y., Davanagere, H.J., Hussain, J. and Al-antari, M.A., 2024. Deep ensemble transfer learning framework for COVID-19 Arabic text identification via deep active learning and text data augmentation. Multimedia Tools and Applications, pp.1-39. [link]

1. [18]
   Al-antari, M.A., Shaaf, Z.F., Jamil, M.M.A., Samee, N.A., Alkanhel, R., Talo, M. and Al-Huda, Z., 2024. Deep learning myocardial infarction segmentation framework from cardiac magnetic resonance images. Biomedical Signal Processing and Control, 89, p.105710. [link]

1. [19]
   Malik, I., Iqbal, A., Gu, Y.H. and Al-antari, M.A., 2024. Deep Learning for Alzheimer’s Disease Prediction: A Comprehensive Review. Diagnostics, 14(12), p.1281. [link]

1. [20]
   Addo, D., Zhou, S., Sarpong, K., Nartey, O.T., Abdullah, M.A., Ukwuoma, C.C. and Al-antari, M.A., 2024. A hybrid lightweight breast cancer classification framework using the histopathological images. Biocybernetics and Biomedical Engineering, 44(1), pp.31-54. [link]

1. [1]
   Kvak, Daniel, Anna Chromcová, Robert Hrubý, Eva Janů, Marek Biroš, Marija Pajdaković, Karolína Kvaková, Mugahed A. Al-Antari, Pavlína Polášková, and Sergei Strukov. "Leveraging Deep Learning Decision-Support System in Specialized Oncology Center: A Multi-Reader Retrospective Study on Detection of Pulmonary Lesions in Chest X-ray Images." Diagnostics 13, no. 6 (2023): 1043.

1. [2]
   Alphonse, A. Sherly, JV Bibal Benifa, Abdullah Y. Muaad, Channabasava Chola, Md Belal Bin Heyat, Belal Abdullah Hezam Murshed, Nagwan Abdel Samee, Maali Alabdulhafith, and Mugahed A. Al-Antari. "A Hybrid Stacked Restricted Boltzmann Machine with Sobel Directional Patterns for Melanoma Prediction in Colored Skin Images." Diagnostics 13, no. 6 (2023): 1104.

1. [3]
   Al-Haidri, Walid, Igor Matveev, Mugahed A. Al-Antari, and Mikhail Zubkov. "A Deep Learning Framework for Cardiac MR Under-Sampled Image Reconstruction with a Hybrid Spatial and k-Space Loss Function." Diagnostics 13, no. 6 (2023): 1120.

1. [4]
   Farhan, Abobaker MQ, Shangming Yang, Abdulrahman QS Al-Malahi, and Mugahed A. Al-antari. "MCLSG: Multi-modal classification of lung disease and severity grading framework using consolidated feature engineering mechanisms." Biomedical Signal Processing and Control 85 (2023): 104916.

1. [5]
   Al-Huda, Zaid, Bo Peng, Riyadh Nazar Ali Algburi, Mugahed A. Al-antari, AL-Jarazi Rabea, and Donghai Zhai. "A hybrid deep learning pavement crack semantic segmentation." Engineering Applications of Artificial Intelligence 122 (2023): 106142.

1. [6]
   Anaam, Asaad, Mugahed A. Al-Antari, Jamil Hussain, Nagwan Abdel Samee, Maali Alabdulhafith, and Akio Gofuku. "Deep Active Learning for Automatic Mitotic Cell Detection on HEp-2 Specimen Medical Images." Diagnostics 13, no. 8 (2023): 1416.

1. [7]
   Ukwuoma, C. C., Cai, D., Heyat, M. B. B., Bamisile, O., Adun, H., Al-Huda, Z., & Al-antari, M. A. (2023). Deep Learning Framework for Rapid and Accurate Respiratory COVID-19 Prediction Using Chest X-ray Images. Journal of King Saud University-Computer and Information Sciences, 101596.

1. [1]
   Mugahed A. Al-antari et al. "Arabic Document Classification: Performance Investigation of Preprocessing and Representation Techniques." Mathematical Problems in Engineering (SCIE, Q2), 2022.

1. [2]
   Mugahed A. Al-antari et al., "Gender Identification and Classification of Drosophila melanogaster Flies Using Machine Learning Techniques." Computational and Mathematical Methods in Medicine (SCIE, Q2), 2022.

1. [3]
   Mugahed A. Al-antari et al., “Artificial Intelligence-Based Approach for Misogyny and Sarcasm Detection from Arabic Texts”, Computational Intelligence and Neuroscience (SCIE, [Q1]), Vol. 2022, no. --, pp. … - …, 2022, [link]

1. [4]
   Mugahed A. Al-antari et al., “A Hybrid Deep Transfer Learning of CNN-Based LR-PCA for Breast Lesion Diagnosis via Medical Breast Mammograms”, Sensors 2022, 22, 4938. [link]

1. [5]
   AlElaiwi, Mohammad, Mugahed A. Al-antari, Hafiz Farooq Ahmad, Areeba Azhar, Badar Almarri, and Jamil Hussain. "VPP: Visual Pollution Prediction Framework Based on a Deep Active Learning Approach Using Public Road Images." Mathematics 11, no. 1 (2023): 186.

1. [6]
   Al-Tam, R. M., Al-Hejri, A. M., Narangale, S. M., Samee, N. A., Mahmoud, N. F., Al-Masni, M. A., & Al-Antari, M. A. (2022). A Hybrid Workflow of Residual Convolutional Transformer Encoder for Breast Cancer Classification Using Digital X-ray Mammograms. Biomedicines, 10(11), 2971.

1. [7]
   Abdu, Ahmed, Zhengjun Zhai, Redhwan Algabri, Hakim A. Abdo, Kotiba Hamad, and Mugahed A. Al-antari. "Deep Learning-Based Software Defect Prediction via Semantic Key Features of Source Code—Systematic Survey." Mathematics 10, no. 17 (2022): 3120.

1. [8]
   Lee, Soojeong, Hyeonjoon Moon, Mugahed A. Al-Antari, and Gangseong Lee. "Dual-Sensor Signals Based Exact Gaussian Process-Assisted Hybrid Feature Extraction and Weighted Feature Fusion for Respiratory Rate and Uncertainty Estimations." Sensors 22, no. 21 (2022): 8386.

1. [9]
   Al-Hejri, Aymen M., Riyadh M. Al-Tam, Muneer Fazea, Archana Harsing Sable, Soojeong Lee, and Mugahed A. Al-Antari. "ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images." Diagnostics 13, no. 1 (2022): 89.

1. [10]
   Samee, Nagwan Abdel, Ghada Atteia, Souham Meshoul, Mugahed A. Al-antari, and Yasser M. Kadah. "Deep Learning Cascaded Feature Selection Framework for Breast Cancer Classification: Hybrid CNN with Univariate-Based Approach." Mathematics 10, no. 19 (2022): 3631.

1. [11]
   Tripathi, Pragati, M. A. Ansari, Tapan Kumar Gandhi, Rajat Mehrotra, Md Belal Bin Heyat, Faijan Akhtar, Chiagoziem C. Ukwuoma, Mugahed A. Al-antari, "Ensemble Computational Intelligent for Insomnia Sleep Stage Detection via the Sleep ECG Signal." IEEE Access 10 (2022): 108710-108721.

1. [12]
   Chola, C., Muaad, A.Y., Bin Heyat, M.B., Benifa, J.B., Naji, W.R., Hemachandran, K., Mahmoud, N.F., Samee, N.A., Al-Antari, M.A., Kadah, Y.M. and Kim, T.S., 2022. BCNet: A Deep Learning Computer-Aided Diagnosis Framework for Human Peripheral Blood Cell Identification. Diagnostics, 12(11), p.2815.

1. [13]
   Ukwuoma, Chiagoziem C., Zhiguang Qin, Md Belal Bin Heyat, Faijan Akhtar, Olusola Bamisile, Abdullah Y. Muaad, Daniel Addo, and Mugahed A. Al-Antari. "A hybrid explainable ensemble transformer encoder for pneumonia identification from chest X-ray images." Journal of Advanced Research (2022).

1. [1]
   Edwin Valarezo, Patricio Lopez, Nahyeon Park, Jiheon Oh, Gahyeon Ryu, Mugahed A. Al-antari, Tae-Seong Kim, “Natural Object Manipulation Using Anthropomorphic Robotic Hand Through Deep Reinforcement Learning and Deep Grasping Probability Network”, Applied Intelligence, vol. 51, no. 2, pp. 1041-1055, 2021, https://doi.org/10.1007/s10489-020-01870-6, (SCI, [Q2]).

1. [2]
   Abdullah Y. Muaad, Hanumanthappa Jayappa, Mugahed A. Al-antari*, and Sungyoung Lee. ArCAR: A Novel Deep Learning Computer-Aided Recognition for Character-Level Arabic Text Representation and Recognition. Algorithms 2021, 14, 216. https:// doi.org/10.3390/a14070216.(SCOPUS, SCIE,[Q2])

1. [3]
   Mugahed A. Al-antari*, Cam-Hao Hua, Jaehun Bang, Sungyoung Lee*, “Fast Deep Learning Computer-Aided Diagnosis against the Novel COVID-19 pandemic from Digital Chest X-ray Images”, Applied Intelligence (SCI, [Q2]), Vol. 51 no. 5, pp. 2890-2907, 2021, [link]

1. [1]
   Mugahed A. Al-antari, Seung-Moo. Han, Tae-Seong Kim, “Evaluation of Deep Learning Detection and Classification towards Computer-aided Diagnosis of Breast Lesions in Digital X-ray Mammograms”, Computer Methods and Programs in Biomedicine, vol. 196, pp. 105584, 2020. (SCI, [Q1]).

1. [1]
   Mugahed A. Al-antari, Mohammed A. Al-masni, Mohamed K. Mettwally, Dildar Hussain, Se-Je Park, Jeong-Sik Shin, Seung-Moo. Han, Tae-Seong Kim, “Denoising images of dual energy X-ray absorptiometry using non-local means filters”, Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 395-412, 2018. (SCIE).

1. [2]
   Dildar Hussain, Mugahed A. Al-antari, Mohammed A. Al-masni, Seung-Moo. Han, Tae-Seong Kim, “Femur segmentation in DXA imaging using a machine learning decision tree”, Journal of X-Ray Science and Technology, vol. 26, no. 05, pp. 727 - 746, 2018. (SCIE).

1. [3]
   Mohammed A. Al-masni⚚, Mugahed A. Al-antari⚚, Jeong-Min Park, Geon Gi, Tae-Yeon Kim, Patricio Rivera, Edwin Valarezo, Mun-Take Choi, Seung-Moo. Han, Tae-Seong Kim, “Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system”, Computer Methods and Programs in Biomedicine, vol. 157, pp. 85-94, 2018. (SCI, [Q1]).

1. [4]
   Mohammed A. Al-masni⚚, Mugahed A. Al-antari⚚, Mun-Take Choi, Seung-Moo. Han, Tae-Seong Kim, “Skin Lesion Segmentation in Dermoscopy Images via Deep Full Resolution Convolutional Networks”, Computer Methods and Programs in Biomedicine, vol. 162, pp. 221-231, 2018. (SCI, [Q1)).

1. [5]
   Mugahed A. Al-antari, Mohammed A. Al-masni, Mun-Take Choi, Seung-Moo. Han, Tae-Seong Kim, “A Fully Integrated Computer-Aided Diagnosis System for Digital X-Ray Mammograms via Deep Learning Detection, Segmentation, and Classification”, International Journal of Medical Informatics, vol. 117, pp. 44 - 54, 2018. (SCI, [Q1]).

1. [1]
   Mugahed A. Al-antari, Mohammed A. Al-masni, Sung-Un Park, JunHyeok Park, Mohamed K. Metwally, Yasser M. Kadah, Seung-Moo Han, Tae-Seong Kim, “An Automatic Computer-Aided Diagnosis System for Breast Cancer in Digital Mammograms via Deep Belief Network,” Journal of Medical and Biological Engineering (JMBE), vol. 38, no. 3, pp. 443 - 456, 2017. (SCIE)

1. [2]
   Mohammed A. Al-masni⚚, Mugahed A. Al-antari⚚, Mohamed K. Mettwally, Yasser M. Kadah, Seung-Moo. Han, Tae-Seong Kim, “A rapid algebraic 3D volume image reconstruction technique for cone beam computed tomography”, Biocybernetics and biomedical engineering, vol. 37, no. 04, pp. 616-629, 2017. (SCIE).