Publications

1. Nashid, S., Siddiqua, A., Mashaka, G. P., Olaniran, A., & Zohora, F. T. (2026). Smart healthcare informatics and AI-based MHAMFD framework for fraud detection in the American health system. International Journal of Advances in Life Science and Technology, 10(1), 1–19. https://doi.org/10.18488/72.v10i1.4936 

2. Islam Ridoy, M. J., Al Mamun, M., Zohora, F. T., Suleiman, Y. A. A., Ejeta, L. F., Akter, M. H., & Farouk, A.-E. (n.d.). Artificial intelligence in cancer metastasis prediction: Models, data modalities, and methodological quality. Manuscript submitted to Bulletin of the National Research Centre (SpringerLink). Status: Under Review. Submission ID: d1191e57-b5d3-4202-a689-440c69776026

3. Nashid, S., Jahan, I., Akther, V., Munni, A., Al Mamun, M., Suleiman, Y. A. A., Zohora, F. T., & Farouk, A.-E. (n.d.). Explainable and trustworthy machine learning for chronic kidney disease diagnosis: A large-scale data science analysis of U.S. clinical records. Manuscript submitted to the International Journal of Data Science and Analytics (Springer Nature). Status: Under Review. Submission ID: f10101f7-fa30-4065-8625-d4414fa55f34

Ongoing Projects

1. Artificial Intelligence in Women’s Health: Clinical Applications, Evidence Gaps, and Pathways to Equitable Translation (Registration Ongoing)

2. From Prediction to Practice: Clinical Validation and Implementation of Artificial Intelligence in Women’s Health. Scientifically, the most distinctive companion; if pursued, shorten Section 5 here and cross-reference it (Registration Not Open)

3. Equity, Bias, and Responsible Artificial Intelligence in Women’s Health (Registration Not Open)

4. AI in maternal and obstetric health (Registration Not Open).