Privacy in Social Media
Davazdahemami, B., Zolbanin, HM., Delen, D., An Explanatory Machine Learning Framework for Studying Pandemics: The Case of COVID-19 Emergency Department Readmissions (2022). Decision Support Systems (forthcoming)
Davazdahemami, B., Zolbanin, HM., Delen, D., An explanatory analytics for early detection of chronic risk factors in pandemics (2022). Healthcare Analytics, 100020. https://bit.ly/3nnlOHf
Davazdahemami, B., Peng, P., Delen, D., A deep learning approach for predicting early bounce-backs to the emergency departments (2022). Healthcare Analytics, 100018. https://bit.ly/3GB19He
Zolbanin, H.M., Hassan Zadeh, A., Davazdahemami, B. Miscommunication in the Age of Communication: A Crowdsourcing Framework for Symptom Surveillance at the Time of Pandemics (2021). International journal of medical informatics, 151, 104486.
Eryarsoy, E., Delen, D., Davazdahemami, B.., Topuz, K. A Novel Diffusion-Based Approach to Estimating Cases, Hospitalizations, and Fatalities in Epidemics: The Case of COVID-19 (2021). Journal of Business Research 124, 163-178 https://bit.ly/3lZUjjr
Eryarsoy, E., Davazdahemami, B., Delen, D., Adjusting COVID-19 Reports for Age Disparities: A Framework for Transferring Knowledge between Affected Countries and Comparing their Reporting Performances (2020) . https://www.medrxiv.org/content/10.1101/2020.08.31.20185223v1
Davazdahemami, Hammer, B., B., Kalgotra, P., Luse, A., From General to Situational Privacy Concerns: A New Mechanism to Explain Information Disclosure in Social Networks (2020). Communications of Association of Information Systems 47(1) . https://doi.org/10.17705/1CAIS.04730
Delen, D., Eryarsoy, E., Davazdahemami, B. (2020). No Place like Home: Cross-National Data Analysis of the Efficacy of Social Distancing during the COVID-19 Pandemic. JMIR Public Health and Surveillance 2020;6(2):e19862 (Full text available at: https://doi.org/10.2196/19862 )
Zolbanin, H. M., Davazdahemami, B., Delen, D., & Zadeh, A. H. (2020). Data analytics for the sustainable use of resources in hospitals: Predicting the length of stay for patients with chronic diseases. Information & Management, 103282.
Delen, D., Davazdahemami, B., Eryarsoy, E., Tomak, L., Valluru, A. (2020) Using Predictive Analytics to Identify Drug-Resistant Epilepsy Patients. Health Informatics Journal 26 (1), 449-460.
Davazdahemami, B., Delen, D. (2019). Examining the Effect of Prescriptions Sequence on Developing Adverse Drug Reactions; the Case of Renal Failure in Diabetic Patients. International Journal of Medical Informatics, 125, 62-70.
Davazdahemami, B., & Delen, D. (2019). The confounding role of common diabetes medications in developing acute renal failure: A data mining approach with emphasis on drug-drug interactions. Expert Systems with Applications, 123, 168-177.
Davazdahemami, B., Hammer, B., Luse, A., Kalgotra, P. (2018) The Role of Parallelism in Resolving the Privacy Paradox of Information Disclosure in Social Networks. Proceedings of thirty ninth International Conference on Information Systems (ICIS) 2018. (Available at: https://aisel.aisnet.org/icis2018/security/Presentations/5/ )
Davazdahemami, B., Delen, D. (2018) A Chronological Pharmacovigilance Network Analytics Approach for Predicting Adverse Drug Events. Journal of the American Medical Informatics Association (JAMIA), Volume 25, Issue 10, 1 October 2018, Pages 1311–1321. (Available online: https://goo.gl/7FE7nR )
Davazdahemami, B., Luse, A., Scheibe, K., Townsend, A. (2018) Training, Self-Efficacy, and Performance; a Replication Study. AIS Transactions on Replication Research 4, no. 1 (2018): 3.
Davazdahemami, B., Hammer, B., & Soror, A. (2016, January). Addiction to mobile phone or addiction through mobile phone? In System Sciences (HICSS), 2016 49th Hawaii International Conference on (pp. 1467-1476). IEEE.
Azadeh, A., Davazdahemami, B. (2012) An Integrated Artificial Neural Network Approach for Predicting Internet Penetration Rate. 25th European Conference of Operational Research, 2012- Vilnius, Lithuania.
Rabbani, M., Davazdahemami, B., Manavizadeh, N. (2010) A Mathematical Model and Two Genetic Algorithms for Balancing Mixed-Model Two-Sided Assembly Lines with Multifunctional Workers Assignment. Proceedings of 7th International Industrial Engineering Conference 2010, Isfahan- Iran.
Manuscripts Under Review
Davazdahemami, B., Peng, P., Delen, D. Predicting Early Bounce-backs to the Emergency Department: A Deep Learning Approach. ACM Transactions on Management Information Systems (under review)
Zolbanin, H., Davazdahemami, B., H. Zadeh, A. Miscommunication in the Age of Communication: A Crowdsourcing Framework for Symptom Surveillance at the Time of Pandemics. Decision Support Systems (Under Review)
Davazdahemami, B., Zolbanin, H.M., Delen, D. An Explanatory Machine Learning Framework for Studying Pandemics: The Case of COVID-19 Emergency Department Readmissions. Decision Support Systems (Under Review)
Ongoing Research Projects
Davazdahemami, B., Delen, D. A Deep Learning Approach for Extracting Relations between Mentions of Drugs and Events in the Social Media Text. Target: JAMIA.
Delen. D., Davazdahemami, B. An Introduction to Deep Learning (Book Chapter for the new edition of “Business Intelligence, Analytics, and Data Science: A Managerial Perspective” book by Sharda, Delen, and Turban; Pearson; ISBN: 0134633288).
Davazdahemami, B., Zolbanin, H., Delen, D. An Optimized Machine Learning Approach to Predict Early Readmission of COVID-19 Patients.