Publications

Journals

Vega, L., Conneen, W., Veronin, M., Schumaker, R., (2024). A Neural Network Approach to Predicting Opioid Abuse Using Patient Diagnosis and Prescription History. PLOS One. Forthcoming

Schumaker, R., Veronin, M., Rohm, T., Boyett, M. and Dixit, R., (2021). A Data Driven Approach to Profile Potential SARS-CoV-2 Drug Interactions Using TylerADE. Journal of International Technology and Information Management. 30(3)

Veronin, M., Schumaker, R., Dixit, R., Dhake, P., Mason, D. and Ogwo, M., (2020). A Systematic Approach to Cleaning of Drug Name Records in the FAERS Database. International Journal of Big Data Management. 1(2):105-118

Veronin, M., Schumaker, R. and Dixit, R., (2020). The Irony of MedWatch and the FAERS Database: An Assessment of Data Input Errors and Potential Consequences. The Journal of Pharmacy Technology. 36(4)

Aljawarneh, S., Bayat, O., Lara, J. and Schumaker, R., (2020). Machine Learning Designs, Implementations and Techniques. IEEE Access. 8(1):120548-120552

Veronin, M., Schumaker, R., Dixit, R. and Elath, H., (2019). Opioids and Frequency Counts in the US Food and Drug Administration Adverse Event Reporting System (FAERS) Database: A Quantitative View of the Epidemic. Drug; Healthcare and Patient Safety. 2019(11):65:70

Veronin, M. and Schumaker, R., (2019). Opioid Adjunct Drug Therapy: Evaluating Effectiveness Using Text Analytics of Real World Data. Communications of the IIMA. 17(1)

Schumaker, R. and Reganti, K., (2014). Implementation of Electronic Health Record (EHR) System in Healthcare Industry. International Journal of Privacy and Health Information Management. 2(2):57-71

Conferences

Schumaker, R., Dixit, R., Veronin, M., Rohm, T., Aljawarneh, S. and Lara, J., (2021). An Analysis of COVID-19 Vaccine Allergic Reactions. International Information Management Association Conference (IIMA-2021). October, 2021. Utrecht, Netherlands

De Almeida Rocha, R., Gopalakrishna-Remani, V., Fischer, M., Lamichhane, R. and Schumaker, R., (2020). Impact of the Length of Stay on Readmission Percentage and Determination of Cohort of Patients and Influence of Length of Stay on Readmission Rates to Decide Resource Allocation and Reduce Financial Impact for a Texas Not For Profit Healthcare System. The 50th Annual Meeting of the Southwest Decision Support Institute (SWDSI-2020). March 2020. San Antonio, TX

Shamburger, D., Gopalakrishna-Remani, V., Fischer, M. and Schumaker, R., (2020). Impact of the Length of Stay, Cohort of Patients and Age on Wheelchair Mode of Transportation at a Texas Not-for-Profit Healthcare System. The 50th Annual Meeting of the Southwest Decision Support Institute (SWDSI-2020). March 2020. San Antonio, TX

Veronin, M. and Schumaker, R., (2019). Opioid Adjunct Drug Therapy: Evaluating Effectiveness Using Text Analytics of Real World Data. International Information Management Association (IIMA-2019). September 2019. New Rochelle, NY

Veronin, M., Schumaker, R., Dixit, R. and Ogwo, M., (2018). Irony of the FAERS Database: An Analysis of Data Input Errors and Potential Consequences. 29th Annual Conference of the International Information Management Association (IIMA-2018). October 2018. Houston, TX

Dixit, R., Schumaker, R. and Veronin, M., (2018). A Decision Tree Analysis of Opiod and Prescription Drug Interactions Leading to Death Using the FAERS Database. 29th Annual Conference of the International Information Management Association (IIMA-2018). October 2018. Houston, TX

Elath, H., Schumaker, R. and Veronin, M., (2018). Predicting Deadly Drug Combinations through a Machine Learning Approach. Pacific Asia Conference on Information Systems (PACIS-2018). June 2018. Yokohama, Japan

Schumaker, R., Veronin, M., Dixit, R., Dhake, P. and Mason, D., (2017). Calculating a Severity Score of an Adverse Drug Reaction Using SVR on the FAERS Database. 28th Annual Conference of the International Information Management Association (IIMA-2017). September 2017. Glasgow, Scotland

Book Chapters

Veronin, M., Schumaker, R., Dixit, R. and Elath, H., (2022). “Opioids and Frequency Counts in the US Food and Drug Administration Adverse Event Reporting System (FAERS) Database,” in Elshimali; J., Current Aspects in Pharmaceutical Research and Development Volume 8, pp 35-43 London- BP International

Schumaker, R. and Reganti, R., (2016). “Implementation of Electronic Health Record (EHR) System in the Healthcare Industry,” in Information Resources Management Association, E-Health and Telemedicine: Concepts; Methodologies; Tools; and Applications, pp 1001-1016 Hershey; PA- IGI Global

Posters and Demonstrations

Vega, L., Conneen, W., Veronin, M., Schumaker, R., (2023). A Neural Network Approach to Predicting Opioid Abuse Using Patient Diagnosis and Prescription History. 58th National Collegiate Honors Council Annual Conference, November 2023. Chicago, IL.

Boyett, C., Schumaker, R. and Veronin, M., (2020). Effects of Adjuncts on Opioids. Fifth Annual Research Lyceum at the University of Texas at Tyler, April 2020. Tyler, TX.

Prasun, P., Schumaker, R. and Veronin, M., (2019). Individual vs Combination Drug Effects Using FAERS Database. Fourth Annual Research Lyceum at the University of Texas at Tyler, April 2019. Tyler, TX.

Cisneros, E., Schumaker, R. and Veronin, M., (2019). Discovering Safer Drug Combination Alternatives Using FAERS. Fourth Annual Research Lyceum at the University of Texas at Tyler, April 2019. Tyler, TX.

Ogwo, M., Dixit, R., Schumaker, R. and Veronin, M., (2018). Deaths Associated with Opioids Reported in the FAERS Database. Third Annual Research Lyceum at the University of Texas at Tyler, April 2018. Tyler, TX.

Mason, D., Schumaker, R., Veronin, M., Dixit, R., Dhake, P., Elath, H. and Scoggins, A., (2018). Standardizing the FDA Adverse Reporting System (FAERS) Database. Third Annual Research Lyceum at the University of Texas at Tyler, April 2018. Tyler, TX.

Dixit, R., Schumaker, R., Veronin, M. and Dhake, P., (2018). A Decision Tree Analysis of Opiod and Prescription Drug Interactions Leading to Death Using the FAERS Database. Third Annual Research Lyceum at the University of Texas at Tyler, April 2018. Tyler, TX.

Ogwo, M., Dixit, R., Schumaker, R. and Veronin, M., (2018). Deaths Associated with Opioids Reported in the FAERS Database. American Society of Health-System Pharmacists Midyear Clinical Meeting and Exhibition, December 2018. Anaheim, CA.

Mason, D., Schumaker, R., Veronin, M., Dixit, R., Dhake, P., Elath, H. and Scoggins, A., (2017). Standardizing the FDA Adverse Reporting System (FAERS) Database. 52nd National Collegiate Honors Council Annual Conference, November 2017. Atlanta, GA.

Under Review

Dixit, R., Veronin, M. and Schumaker, R., Determining Mortality Likelihood of Opioid Drug Combinations using Decision Tree Analysis. IEEE Access.

Prince, M., Veronin, M. and Schumaker, R., Prediction of Unknown Drug Combinations Causing Adverse Reactions. Ninth Annual Research Lyceum at the University of Texas at Tyler.

Prince, M., Veronin, M. and Schumaker, R., Prediction of Unknown Drug Combinations Causing Adverse Reactions. LSU Shreveport Regional Student Scholars Forum (LSUS-2024).

Vega, L., Veronin, M. and Schumaker, R., A Neural Network Approach to Predicting Opioid Misuse Using Patient Diagnosis and Prescription History. LSU Shreveport Regional Student Scholars Forum (LSUS-2024).

Papers In Progress

Schumaker, R., Veronin, M. and Dixit, R., Machine Learning the FAERS Database to Predict Unknown Deadly Drug Combinations. ACM Transactions on Information Systems.

Schumaker, R., Veronin, M. and Dixit, R., An Automatic System to Identify Adverse Drug Reaction Severity for n-Drug Combinations. Data Mining and Knowledge Discovery.

Schumaker, R., Veronin, M. and Dixit, R., Predicting Adverse n-Drug Reactions in Cardiovascular Events: A Machine Learning Investigation of the FAERS Database. Journal of Biomedical Informatics.

Permanent link to this article: https://robschumaker.com/pubs/