Gradients of Fear and Anger in the Social Media Response to Terrorism. - Matthew Baucum; Richard John (HICSS, 2019)

Hidden Markov models are recurrent neural networks: A disease progression modeling application. - Matt Baucum; Anahita Khojandi; Theodore Papamarkou (CoRR, 2020)

Temporal and Geospatial Gradients of Fear and Anger in Social Media Responses to Terrorism. - Matthew Baucum; Jinshu Cui; Richard S. John (ACM Trans. Soc. Comput., 2020)

Hidden Markov models as recurrent neural networks: An application to Alzheimer's disease. - Matt Baucum; Anahita Khojandi; Theodore Papamarkou (BIBE, 2021)

Predicting Severity in People with Aphasia: A Natural Language Processing and Machine Learning Approach. - Marjory Day; Rupam Kumar Dey; Matthew Baucum; Eun Jin Paek; Hyejin Park; Anahita Khojandi (EMBC, 2021)

Using Verb Fluency, Natural Language Processing, and Machine Learning to Detect Alzheimer's Disease. - Aradhana Soni; Benjamin Amrhein; Matthew Baucum; Eun Jin Paek; Anahita Khojandi (EMBC, 2021)

Improving Deep Reinforcement Learning With Transitional Variational Autoencoders: A Healthcare Application. - Matthew Baucum; Anahita Khojandi; Rama K. Vasudevan (IEEE J. Biomed. Health Informatics, 2021)

Optimizing Substance Use Treatment Selection Using Reinforcement Learning. - Matt Baucum; Anahita Khojandi; Carole Myers; Larry Kessler (ACM Trans. Manag. Inf. Syst., 2023)

Optimizing Patient-Specific Medication Regimen Policies Using Wearable Sensors in Parkinson's Disease. - Matt Baucum; Anahita Khojandi; Rama K. Vasudevan; Ritesh A. Ramdhani (Manag. Sci., 2023)

Reducing Overdose Deaths and Mitigating County Disparities: Optimal Allocation of Substance Use Treatment Centers. - Matt Baucum; Matt Harris; Lawrence Kessler; Guanyi Lu (Manuf. Serv. Oper. Manag., 2025)