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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)

Lara, J., de Sojo, A., Aljawarneh, S., Schumaker, R. and Al-Shargabi, B., (2020). Developing Big Data Projects in Open University Engineering Courses:Lessons Learned. IEEE Access. 8(1):22988-23001

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., Maida, N., (2018). A Descriptive Analysis of Abnormal Stock Price Movement Following Financial News Article Release. Communications of the International Information Management Association. 16(1)

Schumaker, R., (2018). Machine Learning the Harness Track: A Temporal Investigation of Race History on Prediction. Journal of International Technology and Information Management. 27(2)

Labedz Jr, C. and Schumaker, R., (2018). What do Publicly Available Soccer Match Data Actually Tell Us. Communications of the International Information Management Association. 16(3)

Schumaker, R., Labedz Jr., C., Brown, L. and Jarmoszko, A. T., (2017). Prediction from Regional Angst – A Study of NFL Sentiment in Twitter Using Stock Market Charting. Decision Support Systems. 98(6):80-88

Schumaker, R., Jarmoszko, A. T. and Labedz Jr., C., (2016). Predicting Wins and Spread in the Premier League Using a Sentiment Analysis of Twitter. Decision Support Systems. 88(8):76-84

Grenier, E., Fair, C. and Schumaker, R., (2014). Social Media – Is it a Valid Source for Creating New Business?. Journal of Creative Communications. 9(2):147-159

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

Schumaker, R., (2013). Data Mining the Harness Track and Predicting Outcomes. Journal of International Technology and Information Management. 22(2):103-107

Schumaker, R., (2013). Machine Learning the Harness Track- Crowdsourcing and Varying Race History. Decision Support Systems. 54(3):1370-1379

Schumaker, R., Zhang, Y., Huang, C. and Chen, H., (2012). Evaluating Sentiment in Financial News Articles. Decision Support Systems. 53(3):458-464

Schumaker, R., (2011). From Data to Wisdom- The Progression of Computational Learning in Text Mining. Communications of the International Information Management Association. 11(1):39-48

Schumaker, R., (2010). Analyzing Parts of Speech and their Impact on Stock Price. Communications of the International Information Management Association. 10(3):1-10

Schumaker, R. and Chen, H., (2010). A Discrete Stock Price Prediction Engine Based on Financial News. IEEE Computer. 43(1):51-56

Schumaker, R. and Chen, H., (2010). Interaction Analysis of the Alice Chatterbot: A Two-Study Investigation of Dialog and Domain Questioning. IEEE Transactions on Systems; Man; and Cybernetics-Part A: Systems and Humans. 40(1):40-51

Schumaker, R. and Chen, H., (2009). Textual Analysis of Stock Market Prediction Using Breaking Financial News- The AZFinText System. Association for Computing Machinery Transactions on Information Systems. 27(2)

Schumaker, R., Solieman, O. and Chen, H., (2009). Sports Knowledge Management and Data Mining. Annual Review of Information Science and Technology. 44

Schumaker, R. and Chen, H., (2009). A Quantitative Stock Price Prediction System based on Financial News. Information Processing and Management. 45(5):571-583

Schumaker, R. and Johnson, J., (2008). An Investigation of SVM Regression to Predict Longshot Greyhound Races. Communications of the International Information Management Association. 8(2):67-82

Schumaker, R. and Chen, H., (2008). Evaluating a News-Aware Quantitative Trader- The Effects of Momentum and Contrarian Stock Selection Strategies. Journal of the American Society for Information Science and Technology. 59(2):247-255

Schumaker, R. and Chen, H., (2007). Leveraging Question Answer Technology to Address Terrorism Inquiry. Decision Support Systems. 43(4):1419-1430

Schumaker, R., Liu, Y., Ginsburg, M. and Chen, H., (2007). Evaluating the Efficacy of a Terrorism Question Answer System- The TARA Project. Communications of the Association for Computing Machinery. 50(7):74-80

Schumaker, R., Liu, Y., Ginsburg, M. and Chen, H., (2006). Evaluating Mass Knowledge Acquisition using the ALICE Chatterbot. International Journal of Human-Computer Studies. 64(11):1132-1140

Schumaker, R., Ginsburg, M., Chen, H. and Liu, Y., (2006). An Evaluation of the Chat and Knowledge Delivery Components of a Low-Level Dialog System- The AZ-ALICE Experiment. Decision Support Systems. 42(4):2236-2246
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., Brown, L., Labedz Jr., C. and Jarmoszko, A.T., (2017). Using Financial Analysis Techniques on Twitter Sentiment to Improve NFL Predictions. Discourse Approaches to Financial Communication (DAFC-2017). July 2017. Lugano, Switzerland

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

Nail, M., Ugone, C., King, C., Schumaker, R. and Conn, M.E., (2016). Predicting Opening Weekend Box Office Success: Using Social Media Sentiment and YouTube Data. 27th Annual Conference of the International Information Management Association (IIMA-2016). September 2016. Taipei, Taiwan

Lopez, H., Perkins, M., Odin, K., Webb, D. and Schumaker, R., (2016). Prediction from Fanbase Opinions – A Study of the League of Legends Community on Twiiter. 27th Annual Conference of the International Information Management Association (IIMA-2016). September 2016. Taipei, Taiwan

Spillman, J., Bustamante, G., Hopkins, T. and Schumaker, R., (2016). Predicting the Outcomes of the 2016 NCAA March Madness Mens Tournament Brackets – A Study of Fan Twitter Sentiment. 27th Annual Conference of the International Information Management Association (IIMA-2016). September 2016. Taipei, Taiwan

Labedz Jr., C., Schumaker, R., Jarmoszko, A. T. and Freeman, D., (2015). Two Subsystems of Eleven Elements: System Dynamics and Other Approaches in Modeling Association Football. International Conference of the System Dynamics Society. July 2015. Cambridge, MA

Maida, N. and Schumaker, R., (2015). Press Release Engineering – Leveraging the Power of Press Releases to Manage Stock Price. 26th Annual Conference of the International Information Management Association (IIMA-2015). October 2015. Chattanooga, TN

Fields, A., Shorthouse, A. and Schumaker, R., (2013). Everything has its Price- Privacy Concerns and Rewards for using Mobile Location. 24th Annual Conference of the International Information Management Association (IIMA-2013). October 2013. New Rochelle, NY

Gagnon, J., Gray, S., Khalaf, L. and Schumaker, R., (2013). How Universities can use Social Media as an Information Tool. 24th Annual Conference of the International Information Management Association (IIMA-2013). October 2013. New Rochelle, NY

Schumaker, R., (2011). From Data to Wisdom- The Progression of Computational Learning in Text Mining. 22nd Annual Conference of the International Information Management Association (IIMA-2011). October 2011. New Orleans, LA

Schumaker, R., (2011). Using SVM Regression to Predict Harness Races- A One Year Study on Northfield Park. Midwest Decision Sciences Institute Conference (Midwest DSI). May 2011. Indianapolis, IN

Schumaker, R., (2010). Analyzing Parts of Speech and their Impact on Stock Price. 21st Annual Conference of the International Information Management Association (IIMA-2010). October 2010. Utrecht, Netherlands

Schumaker, R., (2010). An Analysis of Verbs in Financial News Articles and their Impact on Stock Price. NAACL Workshop on Social Media (#Social Media-2010). June 2010. Los Angeles, CA

Schumaker, R., Zhang, Y. and Huang, C., (2009). Sentiment Analysis of Financial News Articles. 20th Annual Conference of the International Information Management Association (IIMA-2009). October 2009. Houston, TX

Schumaker, R., (2009). Analyzing Representational Schemes of Financial News Articles. The Third China Summer Workshop on Information Systems (CSWIM-2009). June 2009. Guangzhou, China

Schumaker, R. and Johnson, J., (2008). An Investigation of SVM Regression to Predict Longshot Greyhound Races. 19th Annual Conference of the International Information Management Association (IIMA-2008). October, 2008. San Diego, CA

Schumaker, R. and Chen, H., (2006). Textual Analysis of Stock Market Prediction Using Financial News Articles. Americas Conference on Information Systems (AMCIS-2006). August 2006. Acapulco, Mexico

McDonald, D., Chen, H. and Schumaker, R., (2005). Transforming Open-Source Documents to Terror Networks- The Arizona TerrorNet. American Association for Artificial Intelligence Conference Spring Symposium (AAAI-2005). March 2005. Stanford, CA

Reid, E., Qin, J., Chung, W., Xu, J., Zhou, Y., Schumaker, R., Sageman, M. and Chen, H., (2004). Terrorism Knowledge Discovery Project- A Knowledge Discovery Approach to Addressing the Threats of Terrorism. IEEE International Conference on Intelligence and Security Informatics (ISI-2004). June 2004. Tucson, AZ
Books

Schumaker, R., Solieman, O. and Chen, H., (2010). Sports Data Mining- Uncovering New Knowledge and Performance Measures. New York- Springer
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

Schumaker, R. and Chen, H., (2011). “Predicting Stock Price Movement from Financial News Articles,” in Yap; A., IS for Global Financial Markets, pp 96-128 New York- IGI Global

Schumaker, R. and Chen, H., (2006). “Case Study 17- A Dialog System for Terrorism Resources,” in Chen; H., Intelligence and Security Informatics for International Security- Information Sharing and Data Mining, pp 136-139 New York- Springer
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.

Conneen, W., Vega, L., Veronin, M. and Schumaker, R., (2023). Using Artificial Intelligence to Predict Opioid Abuse in Hospital Settings. Eighth Annual Research Lyceum at the University of Texas at Tyler, April 2023. Tyler, TX.

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.

Jarmoszko, A. T., Labedz Jr., C. and Schumaker, R., (2016). Toward a Model of Collective Intelligence of Sporting Teams – Examining Data from the 2014 Soccer World Cup. Collective Intelligence, June 2016. New York, NY.

Schumaker, R., Jarmoszko, A. T., Labedz Jr., C. and Freeman, D., (2015). Predicting Premier League Soccer Using a Sentiment Analysis of Twitter. MIT Sloan Sports Analytics Conference, February 2015. Boston, MA.

Schumaker, R., Chen, H., Wang, T. and Wilkerson, J., (2005). Terror Tracker System- A Web Portal for Terrorism Research. Joint Conference on Digital Libraries (JCDL-2005), June 2005. Denver, CO.

Schumaker, R. and Chen, H., (2005). Question Answer TARA- A Terorrism Activity Resource Application. IEEE International Conference on Intelligence and Security Informatics (ISI-2005), May 2005. 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.