Dr. Jonathan Stubblefield

Assistant Director, Center for No-Boundary Thinking

Education

Research Interests

Dr. Stubblefield’s research seamlessly integrates computer science with human medicine. At Arkansas State University, he has channeled this passion into investigating the intersection of artificial intelligence and medical science. As an assistant professor, Dr. Stubblefield plays a key role in mentoring aspiring scientists. His commitment to leveraging AI to improve community health drives his ongoing pursuit of collaborations that promote scientific advancement and innovation.

Publications in Peer-reviewed Journals

Causey J, Stubblefield J, Qualls J, Fowler J, Cai L, Walker K, Guan Y, Huang X. (2021). An ensemble of U-Net models for kidney tumor segmentation with CT images. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3): 1387-1392. https://doi.org/10.1109/tcbb.2021.3085608

Fowler J, Stubblefield J, Causey J, Qualls J, Dong W, Jiang H, Walker K, Guang Y, Huang X. (2021). Identify differentially expressed genes with large background samples. International Journal of Computational Biology and Drug Design, 14(6), 411-428. https://doi.org/10.1504/ijcbdd.2021.10045802

Stubblefield J, Hervert M, Causey JL, Qualls JA, Dong W, Cai L, Fowler J, Bellis E, Walker K, Moore JH, Nehring S, Huang X. (2020). Transfer Learning with Chest X-Rays for ER Patient Classification. Scientific Reports (10), 20900. https://doi.org/10.1038/s41598-020-78060-4

Causey JL, Li K, Chen X, Dong W, Walker K, Qualls JA, Stubblefield J, Moore JH, Guan Y, Huang X. (2020). Spatial Pyramid Pooling with 3D Convolution Improves Lung Cancer Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19 (2): 1165-1172. https://doi.org/10.1109/tcbb.2020.3027744


Other Publications
Gilbert B, Stubblefield J, Qualls J, Huang X, Pait A, Yanowitz K, Hays A, Richmond E, Parker L, Washington T. (2023). Dyslexia and AI: The Use of Artificial Intelligence to Identify and Create Font to Improve Reading Ability of Individuals With Dyslexia. In E. Langran, P. Christensen & J. Sanson (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 856-865). New Orleans, LA, United States: Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/p/221937/

Zhou W, Bellis ES, Stubblefield J, Causey J, Qualls J, Walker K, Huang XZ. (2019). Minor QTLs Mining through the Combination of GWAS and Machine Learning Feature Selection. BioRxiv (Cold Spring Harbor Laboratory Press). http://dx.doi.org/10.1101/702761