Miller, Timothy

The TRIPOD-LLM reporting guideline for studies using large language models

Gallifant, J., Afshar, M., Ameen, S., Aphinyanaphongs, Y., Chen, S., Cacciamani, G., Demner-Fushman, D., Dligach, D., Daneshjou, R., Fernandes, C., et al. (2025) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 615

Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review

Si, Y., Du, J., Li, Z., Jiang, X., Miller, T., Wang, F., Jim Zheng, W., & Roberts, K. (2021) · Journal of Biomedical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 235

Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records

Savova, G. K., Danciu, I., Alamudun, F., Miller, T., Lin, C., Bitterman, D. S., Tourassi, G., & Warner, J. L. (2019) · Cancer Research

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 170

Fadl Federated-autonomous deep learning for distributed electronic health record

Liu, D., Miller, T., Sayeed, R., & Mandl, K. D. (2018) · arXiv

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 65

A scoping review of publicly available language tasks in clinical natural language processing

Gao, Y., Dligach, D., Christensen, L., Tesch, S., Laffin, R., Xu, D., Miller, T., Uzuner, O., Churpek, M. M., & Afshar, M. (2022) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 28

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Keloth, V. K., Banda, J. M., Gurley, M., Heider, P. M., Kennedy, G., Liu, H., Liu, F., Miller, T., Natarajan, K., V Patterson, O., et al. (2023) · Journal of Biomedical Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 16

Learning Patient Representations from Text

Dligach, D., & Miller, T. (2018) · Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 13

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?

Gao, Y., Myers, S., Chen, S., Dligach, D., Miller, T. A., Bitterman, D., Churpek, M., & Afshar, M. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 8

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes

Derton, A., Guevara, M., Chen, S., Moningi, S., Kozono, D. E., Liu, D., Miller, T. A., Savova, G. K., Mak, R. H., & Bitterman, D. S. (2023) · JCO Clinical Cancer Informatics

Machine Learning in HealthcareComputational and Text Analysis Methods

Cited by 8

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models

Gao, J., Chen, G., O’Rourke, A. P., Caskey, J., Carey, K. A., Oguss, M., Stey, A., Dligach, D., Miller, T., Mayampurath, A., et al. (2024) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 5