• Medical Image Processing
• Machine Unlearning
• Large Language/Vision Models
• Radiogenomics Analysis

First/Corresponding author:

• Koohi-Moghadam, M*., & Bae, K. T. (2023). Generative AI in Medical Imaging: Applications, Challenges, and Ethics. Journal of Medical Systems, 47(1), 94.
• Zhao, D., Homayounfar, M., Zhen, Z., Wu, M.Z., Yin Yu, S., Yiu, K.H., Vardhanabhuti, V., Pelekos, G., Jin, L. and Koohi-Moghadam, M^*., (2022). A Multimodal Deep Learning Approach to Predicting Systemic Diseases from Oral Conditions. Diagnostics, 12(12), p.3192.
• Mohamadi, A., Cheng, T., Jin, L., Wang, J., Sun, H., & Koohi-Moghadam, M^*. (2022). An ensemble 3D deep-learning model to predict protein metal-binding site. Cell Reports Physical Science, 101046.
• Shabani, S., Homayounfar, M., Vardhanabhuti, V., Mahani, M. A. N., & Koohi-Moghadam, M^*. (2022). Self-supervised region-aware segmentation of COVID-19 CT images using 3D GAN and contrastive learning. Computers in Biology and Medicine, 149, 106033.
• Koohi-Moghadam, M., Wang, H., Wang, Y., Yang, X., Li, H., Wang, J., & Sun, H. (2019). Predicting disease-associated mutation of metal-binding sites in proteins using a deep learning approach. Nature Machine Intelligence, 1(12), 561-567.
• Koohi-Moghadam, M., Borad, M. J., Tran, N. L., Swanson, K. R., Boardman, L. A., Sun, H., & Wang, J. (2019). MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers. Bioinformatics, 35(19), 3812-3814.
• Koohi-Moghadam, M. and Rahmani, A.T., 2012, March. Molecular docking with opposition-based differential evolution. In Proceedings of the 27th annual ACM symposium on applied computing (pp. 1387-1392).
• Koohi-Moghadam, M^*., Watt, R.M., Leung. W.L., Multi-site analysis of biosynthetic gene clusters (BGCs) from the periodontitis oral microbiome (Under review, corresponding author). Preprint link: https://www.medrxiv.org/content/10.1101/2023.03.02.23286703v2

Co-author:

• Adeoye, J., Koohi-Moghadam, M., Choi, S. W., Zheng, L. W., Lo, A. W. I., Tsang, R. K. Y., ... & Su, Y. X. (2023). Predicting oral cancer risk in patients with oral leukoplakia and oral lichenoid mucositis using machine learning. Journal of Big Data, 10(1), 1-24.
• Homayounfar, M., Koohi-Moghadam, M., Rawassizadeh, R., & Vardhanabhuti, V. (2023). Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image Analysis. arXiv preprint arXiv:2304.07461.
• Lian, J., Deng, J., Hui, E.S., Koohi-Moghadam, M., She, Y., Chen, C. and Vardhanabhuti, V., (2022). Early stage NSCLS patients’ prognostic prediction with multi-information using transformer and graph neural network model. Elife, 11, p.e80547.
• Zhang, Q., Wang, R., Wang, M., Liu, C., Koohi-Moghadam, M., Wang, H., ... & Sun, H. (2022). Re-sensitization of mcr carrying multidrug resistant bacteria to colistin by silver. Proceedings of the National Academy of Sciences, 119(11), e2119417119.
• Han, Y., Koohi-Moghadam, M., Chen, Q., Zhang, L., Chopra, H., Zhang, J., & Dissanayaka, W. L. (2022). HIF-1α Stabilization Boosts Pulp Regeneration by Modulating Cell Metabolism. Journal of Dental Research, 101(10), 1214-1226.
• Chan, L.C., Zhang, Y., Kuang, X., Koohi-Moghadam, M., Wu, H., Lam, T.Y.C., Chiou, J. and Wen, C., 2022. Captopril Alleviates Chondrocyte Senescence in DOCA-Salt Hypertensive Rats Associated with Gut Microbiome Alteration. Cells, 11(19), p.3173.
• Chau, R. C. W., Chong, M., Thu, K. M., Chu, N. S. P., Koohi-Moghadam, M., Hsung, R. T. C., ... & Lam, W. Y. H. (2022). Artificial intelligence-designed single molar dental prostheses: A protocol of prospective experimental study. PloS one, 17(6), e0268535.
• Zhao, D., Cheng, T., Koohi‐Moghadam, M., Wu, M. Z., Yu, S. Y., Ding, X., ... & Jin, L. (2022). Salivary ACE2 and TMPRSS2 link to periodontal status and metabolic parameters. Clinical and Translational Discovery, 2(1), e37.
• Adeoye, J., Hui, L., Koohi-Moghadam, M., Tan, J. Y., Choi, S. W., & Thomson, P. (2022). Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis. International journal of medical informatics, 157, 104635.
• Adeoye, J., Koohi-Moghadam, M., Lo, A. W. I., Tsang, R. K. Y., Chow, V. L. Y., Zheng, L. W., ... & Su, Y. X. (2021). Deep learning predicts the malignant-transformation-free survival of oral potentially malignant disorders. Cancers, 13(23), 6054.
• Hu, X., Li, H., Ip, T. K. Y., Cheung, Y. F., Koohi-Moghadam, M., Wang, H., ... & Sun, H. (2021). Arsenic trioxide targets Hsp60, triggering degradation of p53 and survivin. Chemical science, 12(32), 10893-10900.
• Dong, M., Kwok, S.H., Humble, J.L., Liang, Y., Tang, S.W., Tang, K.H., Tse, M.K., Lei, J.H., Ramalingam, R., Koohi-Moghadam, M. and Au, D.W.T., (2021). BING, a novel antimicrobial peptide isolated from Japanese medaka plasma, targets bacterial envelope stress response by suppressing cpxR expression. Scientific reports, 11(1), 1-17.
• Adeoye, J., Hui, L., Tan, J. Y., Koohi-Moghadam, M., Choi, S. W., & Thomson, P. (2021). Prognostic value of non-smoking, non-alcohol drinking status in oral cavity cancer. Clinical Oral Investigations, 1-10.
• Wang, H., Yan, A., Liu, Z., Yang, X., Xu, Z., Wang, Y., Wang, R., Koohi-Moghadam, M., Hu, L., Xia, W. and Tang, H., 2019. Deciphering molecular mechanism of silver by integrated omic approaches enables enhancing its antimicrobial efficacy in E. coli. PLoS biology, 17(6), p.e3000292.
• Yang, X., Koohi-Moghadam, M., Wang, R., Chang, Y. Y., Woo, P. C., Wang, J., & Sun, H. (2018). Metallochaperone UreG serves as a new target for design of urease inhibitor: A novel strategy for development of antimicrobials. PLoS biology, 16(1), e2003887.